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Notion uses Apache Hudi to power their core analytics datasets and AI features."]}),"\n",(0,t.jsx)(i.h3,{id:"penn-interactive",children:"Penn Interactive"}),"\n",(0,t.jsxs)(i.p,{children:["The interactive arm of ",(0,t.jsx)(i.a,{href:"https://www.pennentertainment.com/",children:"Penn Entertainment"}),", encompassing Penn Interactive and theScore, is a major player in online and retail sports betting markets in the U.S. and Canada, as well as the sports media sector.Apache Hudi's efficient processing helps them to keep Spark resources reasonable while running hundreds of streaming jobs 24/7."]}),"\n",(0,t.jsx)(i.h3,{id:"robinhood",children:"Robinhood"}),"\n",(0,t.jsx)(i.p,{children:(0,t.jsx)(i.a,{href:"https://www.slideshare.net/BalajiVaradarajan13/rds-data-lake-robinhood",children:"Rds data lake at Robinhood using Apache Hudi"})}),"\n",(0,t.jsx)(i.h3,{id:"sf-express",children:"SF-Express"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.sf-express.com/cn/sc/",children:"SF-Express"})," is the leading logistics service provider in China. HUDI is used to build a real-time data warehouse, providing real-time computing solutions with higher efficiency and lower cost for our business."]}),"\n",(0,t.jsx)(i.h3,{id:"tathastuai",children:"Tathastu.ai"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.tathastu.ai",children:"Tathastu.ai"})," offers the largest AI/ML playground of consumer data for data scientists, AI experts and technologists to build upon. They have built a CDC pipeline using Apache Hudi and Debezium. Data from Hudi datasets is being queried using Hive, Presto and Spark."]}),"\n",(0,t.jsx)(i.h3,{id:"tencent",children:"Tencent"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://intl.cloud.tencent.com/product/emr",children:"EMR from Tencent"})," Cloud has integrated Hudi as one of its BigData components ",(0,t.jsx)(i.a,{href:"https://intl.cloud.tencent.com/document/product/1026/35587",children:"since V2.2.0"}),". Using Hudi, the end-users can handle either read-heavy or write-heavy use cases, and Hudi will manage the underlying data stored on HDFS/COS/CHDFS using Apache Parquet and Apache Avro."]}),"\n",(0,t.jsx)(i.h3,{id:"uber",children:"Uber"}),"\n",(0,t.jsxs)(i.p,{children:["Apache Hudi was originally developed at ",(0,t.jsx)(i.a,{href:"https://uber.com",children:"Uber"}),", to achieve ",(0,t.jsx)(i.a,{href:"http://www.slideshare.net/vinothchandar/hadoop-strata-talk-uber-your-hadoop-has-arrived/32",children:"low latency database ingestion, with high efficiency"}),".\nIt has been in production since Aug 2016, powering the massive ",(0,t.jsx)(i.a,{href:"https://eng.uber.com/uber-big-data-platform/",children:"100PB data lake"}),", including highly business critical tables like core trips,riders,partners. It also\npowers several incremental Hive ETL pipelines and being currently integrated into Uber's data dispersal system."]}),"\n",(0,t.jsx)(i.h3,{id:"udemy",children:"Udemy"}),"\n",(0,t.jsxs)(i.p,{children:["At ",(0,t.jsx)(i.a,{href:"https://www.udemy.com/",children:"Udemy"}),", Apache Hudi on AWS EMR is used to perform ingest MySQL change data capture."]}),"\n",(0,t.jsx)(i.h3,{id:"walmart",children:"Walmart"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://searchdatamanagement.techtarget.com/feature/Hudi-powering-data-lake-efforts-at-Walmart-and-Disney-Hotstar",children:"Walmart"}),"\nchose Apache Hudi to manage their data lake of store transactions."]}),"\n",(0,t.jsx)(i.h3,{id:"yieldsio",children:"Yields.io"}),"\n",(0,t.jsxs)(i.p,{children:["Yields.io is the first FinTech platform that uses AI for automated model validation and real-time monitoring on an enterprise-wide scale. Their ",(0,t.jsx)(i.a,{href:"https://www.yields.io/Blog/Apache-Hudi-at-Yields",children:"data lake"})," is managed by Hudi. They are also actively building their infrastructure for incremental, cross language/platform machine learning using Hudi."]}),"\n",(0,t.jsx)(i.h3,{id:"yotpo",children:"Yotpo"}),"\n",(0,t.jsxs)(i.p,{children:["Using Hudi at Yotpo for several usages. Firstly, integrated Hudi as a writer in their open source ETL framework, ",(0,t.jsx)(i.a,{href:"https://github.com/YotpoLtd/metorikku",children:"Metorikku"})," and using as an output writer for a CDC pipeline, with events that are being generated from a database binlog streams to Kafka and then are written to S3."]}),"\n",(0,t.jsx)(i.h3,{id:"zendesk",children:"Zendesk"}),"\n",(0,t.jsxs)(i.p,{children:["At ",(0,t.jsx)(i.a,{href:"https://www.zendesk.com/",children:"Zendesk"}),", Apache Hudi is adopted for building Data Lake on AWS."]}),"\n",(0,t.jsx)(i.h3,{id:"zto-express",children:"ZTO Express"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.zto.com/",children:"ZTO Express"})," is a large group company integrating express delivery, logistics and other businesses.\nZTO uses Apache Hudi to build a technical architecture integrating lakes and warehouses. As the core of this architecture, Hudi has helped ZTO realize the quasi-real-time update and analysis capabilities of massive data."]})]})}function c(e={}){const{wrapper:i}={...(0,n.R)(),...e.components};return i?(0,t.jsx)(i,{...e,children:(0,t.jsx)(h,{...e})}):h(e)}},28453:(e,i,a)=>{a.d(i,{R:()=>r,x:()=>o});var t=a(96540);const n={},s=t.createContext(n);function r(e){const i=t.useContext(s);return t.useMemo((function(){return"function"==typeof e?e(i):{...i,...e}}),[i,e])}function o(e){let i;return i=e.disableParentContext?"function"==typeof e.components?e.components(n):e.components||n:r(e.components),t.createElement(s.Provider,{value:i},e.children)}}}]); \ No newline at end of file diff --git a/content/assets/js/2dada088.531c8f5b.js b/content/assets/js/2dada088.531c8f5b.js new file mode 100644 index 000000000000..5a9efb7babfa --- /dev/null +++ b/content/assets/js/2dada088.531c8f5b.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkhudi=self.webpackChunkhudi||[]).push([[72421],{98478:(e,a,i)=>{i.r(a),i.d(a,{assets:()=>d,contentTitle:()=>r,default:()=>c,frontMatter:()=>s,metadata:()=>o,toc:()=>l});var t=i(74848),n=i(28453);const s={title:"Powered By",keywords:["hudi","powered-by"],last_modified_at:new Date("2019-12-31T19:59:57.000Z")},r="Who's Using",o={type:"mdx",permalink:"/powered-by",source:"@site/src/pages/powered-by.md",title:"Powered By",description:"Apache Hudi is a fast growing diverse community",frontMatter:{title:"Powered By",keywords:["hudi","powered-by"],last_modified_at:"2019-12-31T19:59:57.000Z"},unlisted:!1},d={},l=[{value:"37 Interactive Entertainment",id:"37-interactive-entertainment",level:3},{value:"Alibaba Cloud",id:"alibaba-cloud",level:3},{value:"Amazon",id:"amazon",level:3},{value:"Amazon Web Services",id:"amazon-web-services",level:3},{value:"Applied Intuition",id:"applied-intuition",level:3},{value:"ByteDance",id:"bytedance",level:3},{value:"Clinbrain",id:"clinbrain",level:3},{value:"DiDi",id:"didi",level:3},{value:"Disney+ Hotstar",id:"disney-hotstar",level:3},{value:"EMIS Health",id:"emis-health",level:3},{value:"Forethought AI",id:"forethought-ai",level:3},{value:"Funding Circle",id:"funding-circle",level:3},{value:"GE Aviation",id:"ge-aviation",level:3},{value:"Grofers",id:"grofers",level:3},{value:"H3C Digital Platform",id:"h3c-digital-platform",level:3},{value:"Halodoc",id:"halodoc",level:3},{value:"Jobtarget",id:"jobtarget",level:3},{value:"Kyligence",id:"kyligence",level:3},{value:"Kuaishou",id:"kuaishou",level:3},{value:"Lingyue-digital Corporation",id:"lingyue-digital-corporation",level:3},{value:"Logical Clocks",id:"logical-clocks",level:3},{value:"Navi",id:"navi",level:3},{value:"NerdWallet",id:"nerdwallet",level:3},{value:"Notion",id:"notion",level:3},{value:"Penn Interactive",id:"penn-interactive",level:3},{value:"Robinhood",id:"robinhood",level:3},{value:"SF-Express",id:"sf-express",level:3},{value:"Tathastu.ai",id:"tathastuai",level:3},{value:"Tencent",id:"tencent",level:3},{value:"Uber",id:"uber",level:3},{value:"Udemy",id:"udemy",level:3},{value:"Walmart",id:"walmart",level:3},{value:"Yields.io",id:"yieldsio",level:3},{value:"Yotpo",id:"yotpo",level:3},{value:"Zendesk",id:"zendesk",level:3},{value:"ZTO Express",id:"zto-express",level:3}];function h(e){const a={a:"a",h1:"h1",h3:"h3",header:"header",p:"p",...(0,n.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(a.header,{children:(0,t.jsx)(a.h1,{id:"whos-using",children:"Who's Using"})}),"\n",(0,t.jsxs)(a.p,{children:["Apache Hudi is a ",(0,t.jsx)(a.a,{href:"https://hudi.apache.org/blog/2022/01/06/apache-hudi-2021-a-year-in-review",children:"fast growing diverse community"}),"\nof people and organizations from all around the globe. The following is a small sample of companies that have adopted or\ncontributed to the Apache Hudi community! ",(0,t.jsx)(a.a,{href:"https://join.slack.com/t/apache-hudi/shared_invite/zt-2ggm1fub8-_yt4Reu9djwqqVRFC7X49g",children:"Join us on slack"}),",\nor come to one of our ",(0,t.jsx)(a.a,{href:"https://hudi.apache.org/community/syncs",children:"virtual community events"}),"."]}),"\n",(0,t.jsx)(a.h3,{id:"37-interactive-entertainment",children:"37 Interactive Entertainment"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.37wan.net/",children:"37 Interactive Entertainment"})," is a global Top20 listed game company, and a leading company on A-shares market of China.\nApache Hudi is integrated into our Data Middle Platform offering real-time data warehouse and solving the problem of frequent changes of data.\nMeanwhile, we build a set of data access standards based on Hudi, which provides a guarantee for massive data queries in game operation scenarios."]}),"\n",(0,t.jsx)(a.h3,{id:"alibaba-cloud",children:"Alibaba Cloud"}),"\n",(0,t.jsxs)(a.p,{children:["Alibaba Cloud provides cloud computing services to online businesses and Alibaba's own e-commerce ecosystem, Apache Hudi is integrated into Alibaba Cloud ",(0,t.jsx)(a.a,{href:"https://www.alibabacloud.com/help/product/70174.htm",children:"Data Lake Analytics"}),"\noffering real-time analysis on hudi dataset."]}),"\n",(0,t.jsx)(a.h3,{id:"amazon",children:"Amazon"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://aws.amazon.com/blogs/big-data/how-amazon-transportation-service-enabled-near-real-time-event-analytics-at-petabyte-scale-using-aws-glue-with-apache-hudi/",children:"Amazon Transportation service"}),"\nuses Apache Hudi for the backbone of their package delivery system, powering petabyte-scale near real time analytics."]}),"\n",(0,t.jsx)(a.h3,{id:"amazon-web-services",children:"Amazon Web Services"}),"\n",(0,t.jsxs)(a.p,{children:["Amazon Web Services is the World's leading cloud services provider. Apache Hudi is ",(0,t.jsx)(a.a,{href:"https://aws.amazon.com/emr/features/hudi/",children:"pre-installed"})," with the AWS Elastic Map Reduce\noffering, providing means for AWS users to perform record-level updates/deletes and manage storage efficiently."]}),"\n",(0,t.jsx)(a.h3,{id:"applied-intuition",children:"Applied Intuition"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.appliedintuition.com/",children:"Applied Intuition"})," accelerates the world\u2019s adoption of safe and intelligent machines. Using Hudi, Applied supports querying across millions of simulations and hours of drive data for their customers. Its table features drastically improve querying performance while maintaining near real-time freshness."]}),"\n",(0,t.jsx)(a.h3,{id:"bytedance",children:"ByteDance"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://hudi.apache.org/blog/2021/09/01/building-eb-level-data-lake-using-hudi-at-bytedance/",children:"ByteDance"}),"\nuses Apache Hudi to power their Exabyte scale TikTok #ForYouPage realtime recommendation engine."]}),"\n",(0,t.jsx)(a.h3,{id:"clinbrain",children:"Clinbrain"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.clinbrain.com/",children:"Clinbrain"})," is the leader of big data platform and usage in medical industry. We have built 200 medical big data centers by integrating Hudi Data Lake solution in numerous hospitals. Hudi provides the ability to upsert and delete on hdfs, at the same time, it can make the fresh data-stream up-to-date efficiently in hadoop system with the hudi incremental view."]}),"\n",(0,t.jsx)(a.h3,{id:"didi",children:"DiDi"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.didiglobal.com/",children:"DiDi"})," is the World\u2018s Leading Transportation Platform. Based on the Hadoop ecosystem, we built a new generation of big data platform based on Apache Hudi, which provides record-level updates/deletes as well as streaming and batch integrated data processing."]}),"\n",(0,t.jsx)(a.h3,{id:"disney-hotstar",children:"Disney+ Hotstar"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://youtu.be/ZamXiT9aqs8",children:"Disney shared"})," how they migrated CDC data to Apache Hudi to power a real-time ads platform for their streaming service."]}),"\n",(0,t.jsx)(a.h3,{id:"emis-health",children:"EMIS Health"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.emishealth.com/",children:"EMIS Health"})," is the largest provider of Primary Care IT software in the UK with datasets including more than 500Bn healthcare records. HUDI is used to manage their analytics dataset in production and keeping them up-to-date with their upstream source. Presto is being used to query the data written in HUDI format."]}),"\n",(0,t.jsx)(a.h3,{id:"forethought-ai",children:"Forethought AI"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://forethought.ai/",children:"Forethought AI"})," is the Leading Generative AI for Customer Support Automation. It unlocks efficiency with the generative AI automation platform that lowers support costs while providing top-tier service in every customer interaction."]}),"\n",(0,t.jsx)(a.h3,{id:"funding-circle",children:"Funding Circle"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.fundingcircle.com/us/",children:"Funding Circle"})," helps people invest in equipment or inventory, consolidate debt, grow their business, or pay business expenses by providing loans."]}),"\n",(0,t.jsx)(a.h3,{id:"ge-aviation",children:"GE Aviation"}),"\n",(0,t.jsx)(a.p,{children:(0,t.jsx)(a.a,{href:"https://aws.amazon.com/blogs/big-data/how-ge-aviation-built-cloud-native-data-pipelines-at-enterprise-scale-using-the-aws-platform/",children:"GE Aviation built cloud-native data pipelines at enterprise scale using Apache Hudi in AWS platform"})}),"\n",(0,t.jsx)(a.h3,{id:"grofers",children:"Grofers"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://grofers.com",children:"Grofers"})," is a grocery delivery provider operating across APAC region. Grofers has ",(0,t.jsx)(a.a,{href:"https://lambda.grofers.com/origins-of-data-lake-at-grofers-6c011f94b86c",children:"integrated hudi"})," in its central pipelines for replicating backend database CDC into the warehouse."]}),"\n",(0,t.jsx)(a.h3,{id:"h3c-digital-platform",children:"H3C Digital Platform"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"http://www.h3c.com/",children:"H3C digital platform"})," provides the whole process capability of data collection, storage, calculation and governance, and enables the construction of data center and data governance ability for medical, smart park, smart city and other industries;\nApache Hudi is integrated in the digital platform to meet the real-time update needs of massive data"]}),"\n",(0,t.jsx)(a.h3,{id:"halodoc",children:"Halodoc"}),"\n",(0,t.jsx)(a.p,{children:(0,t.jsx)(a.a,{href:"https://blogs.halodoc.io/lake-house-architecture-halodoc-data-platform-2-0/",children:"Lake House Architecture at Halodoc: Data Platform 2.0"})}),"\n",(0,t.jsx)(a.h3,{id:"jobtarget",children:"Jobtarget"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.jobtarget.com/",children:"Jobtarget"})," is a company dedicated to helping job seekers and employers connect. This focus has allowed us to earn the opportunity to serve thousands of companies and millions of job seekers each month."]}),"\n",(0,t.jsx)(a.h3,{id:"kyligence",children:"Kyligence"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://kyligence.io/zh/",children:"Kyligence"})," is the leading Big Data analytics platform company. We\u2019ve built end to end solutions for various Global Fortune 500 companies in US and China. We adopted Apache Hudi in our Cloud solution on AWS in 2019. With the help of Hudi, we are able to process upserts and deletes easily and we use incremental views to build efficient data pipelines in AWS. The Hudi datasets can also be integrated to Kyligence Cloud directly for high concurrent OLAP access."]}),"\n",(0,t.jsx)(a.h3,{id:"kuaishou",children:"Kuaishou"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.kuaishou.com/en/",children:"Kuaishou"})," is a prominent Chinese giant in the content community and social platform. The company offers a diverse range of services, including live streaming, short videos, and e-commerce. At Kuaishou, both AI experts and BI technologists leverage Hudi to handle their online business cases. In AI scenarios, Hudi is used to build a unified batch-stream sample lake at the exabyte (EB) scale and end-to-end latency of 30 seconds. The sample lake supports both online and offline training. In BI scenarios, Hudi enhances the traditional HIVE data warehouse by enabling streaming ingestion into the lakehouse at the ODS layer. It efficiently processes append and upsert streams, while also supporting incremental updates across the DWD, DWS, and ADS layers. Currently, Hudi plays a key role in both BI and AI scenarios at Kuaishou."]}),"\n",(0,t.jsx)(a.h3,{id:"lingyue-digital-corporation",children:"Lingyue-digital Corporation"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.lingyue-digital.com/",children:"Lingyue-digital Corporation"})," belongs to BMW Group. Apache Hudi is used to perform ingest MySQL and PostgreSQL change data capture. We build up upsert scenarios on Hadoop and spark."]}),"\n",(0,t.jsx)(a.h3,{id:"logical-clocks",children:"Logical Clocks"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.logicalclocks.com/blog/introducing-the-hopsworks-1-x-series",children:"Hopsworks 1.x series"})," supports Apache Hudi feature groups, to enable upserts and time travel."]}),"\n",(0,t.jsx)(a.h3,{id:"navi",children:"Navi"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://navi.com/",children:"Navi"}),", one of India\u2019s fastest-growing financial service providers, offers Personal & Home Loans, UPI, Insurance, Mutual Funds, and Gold. Powered by Apache Hudi, our Data Platform tech stack has been enhanced to enable near-real-time data ingestion, driving AI/ML initiatives and critical business decisions to create exceptional customer experiences."]}),"\n",(0,t.jsx)(a.h3,{id:"nerdwallet",children:"NerdWallet"}),"\n",(0,t.jsx)(a.p,{children:(0,t.jsx)(a.a,{href:"https://aws.amazon.com/blogs/big-data/how-nerdwallet-uses-aws-and-apache-hudi-to-build-a-serverless-real-time-analytics-platform/",children:"NerdWallet uses AWS and Apache Hudi to build a serverless, real-time analytics platform"})}),"\n",(0,t.jsx)(a.h3,{id:"notion",children:"Notion"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.notion.so/",children:"Notion"})," is the connected workspace where modern teams create and share docs, take notes, manage their projects and time, and organize knowledge \u2014 with AI integrated throughout. Notion uses Apache Hudi to power their core analytics datasets and AI features."]}),"\n",(0,t.jsx)(a.h3,{id:"penn-interactive",children:"Penn Interactive"}),"\n",(0,t.jsxs)(a.p,{children:["The interactive arm of ",(0,t.jsx)(a.a,{href:"https://www.pennentertainment.com/",children:"Penn Entertainment"}),", encompassing Penn Interactive and theScore, is a major player in online and retail sports betting markets in the U.S. and Canada, as well as the sports media sector.Apache Hudi's efficient processing helps them to keep Spark resources reasonable while running hundreds of streaming jobs 24/7."]}),"\n",(0,t.jsx)(a.h3,{id:"robinhood",children:"Robinhood"}),"\n",(0,t.jsx)(a.p,{children:(0,t.jsx)(a.a,{href:"https://www.slideshare.net/BalajiVaradarajan13/rds-data-lake-robinhood",children:"Rds data lake at Robinhood using Apache Hudi"})}),"\n",(0,t.jsx)(a.h3,{id:"sf-express",children:"SF-Express"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.sf-express.com/cn/sc/",children:"SF-Express"})," is the leading logistics service provider in China. HUDI is used to build a real-time data warehouse, providing real-time computing solutions with higher efficiency and lower cost for our business."]}),"\n",(0,t.jsx)(a.h3,{id:"tathastuai",children:"Tathastu.ai"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.tathastu.ai",children:"Tathastu.ai"})," offers the largest AI/ML playground of consumer data for data scientists, AI experts and technologists to build upon. They have built a CDC pipeline using Apache Hudi and Debezium. Data from Hudi datasets is being queried using Hive, Presto and Spark."]}),"\n",(0,t.jsx)(a.h3,{id:"tencent",children:"Tencent"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://intl.cloud.tencent.com/product/emr",children:"EMR from Tencent"})," Cloud has integrated Hudi as one of its BigData components ",(0,t.jsx)(a.a,{href:"https://intl.cloud.tencent.com/document/product/1026/35587",children:"since V2.2.0"}),". Using Hudi, the end-users can handle either read-heavy or write-heavy use cases, and Hudi will manage the underlying data stored on HDFS/COS/CHDFS using Apache Parquet and Apache Avro."]}),"\n",(0,t.jsx)(a.h3,{id:"uber",children:"Uber"}),"\n",(0,t.jsxs)(a.p,{children:["Apache Hudi was originally developed at ",(0,t.jsx)(a.a,{href:"https://uber.com",children:"Uber"}),", to achieve ",(0,t.jsx)(a.a,{href:"http://www.slideshare.net/vinothchandar/hadoop-strata-talk-uber-your-hadoop-has-arrived/32",children:"low latency database ingestion, with high efficiency"}),".\nIt has been in production since Aug 2016, powering the massive ",(0,t.jsx)(a.a,{href:"https://eng.uber.com/uber-big-data-platform/",children:"100PB data lake"}),", including highly business critical tables like core trips,riders,partners. 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b/content/blog/2022/10/17/Get-started-with-Apache-Hudi-using-AWS/index.html index 1d378f54bf61..23128c2fcb8c 100644 --- a/content/blog/2022/10/17/Get-started-with-Apache-Hudi-using-AWS/index.html +++ b/content/blog/2022/10/17/Get-started-with-Apache-Hudi-using-AWS/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2022/11/10/How-Hudl-built-a-cost-optimized-AWS-Glue-pipeline-with-Apache-Hudi-datasets/index.html b/content/blog/2022/11/10/How-Hudl-built-a-cost-optimized-AWS-Glue-pipeline-with-Apache-Hudi-datasets/index.html index d14c743b6e46..b0bc8dac5a19 100644 --- a/content/blog/2022/11/10/How-Hudl-built-a-cost-optimized-AWS-Glue-pipeline-with-Apache-Hudi-datasets/index.html +++ b/content/blog/2022/11/10/How-Hudl-built-a-cost-optimized-AWS-Glue-pipeline-with-Apache-Hudi-datasets/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2022/11/22/Build-your-Apache-Hudi-data-lake-on-AWS-using-Amazon-EMR-Part-1/index.html b/content/blog/2022/11/22/Build-your-Apache-Hudi-data-lake-on-AWS-using-Amazon-EMR-Part-1/index.html index d8036827c0d8..16c9644077ae 100644 --- a/content/blog/2022/11/22/Build-your-Apache-Hudi-data-lake-on-AWS-using-Amazon-EMR-Part-1/index.html +++ b/content/blog/2022/11/22/Build-your-Apache-Hudi-data-lake-on-AWS-using-Amazon-EMR-Part-1/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2022/12/01/Run-apache-hudi-at-scale-on-aws/index.html b/content/blog/2022/12/01/Run-apache-hudi-at-scale-on-aws/index.html index 8ccc7375870b..0850a3eeafbf 100644 --- a/content/blog/2022/12/01/Run-apache-hudi-at-scale-on-aws/index.html +++ b/content/blog/2022/12/01/Run-apache-hudi-at-scale-on-aws/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2022/12/19/Build-Your-First-Hudi-Lakehouse-with-AWS-Glue-and-AWS-S3/index.html b/content/blog/2022/12/19/Build-Your-First-Hudi-Lakehouse-with-AWS-Glue-and-AWS-S3/index.html index 2b214bb47d9f..0e6c632b71f6 100644 --- a/content/blog/2022/12/19/Build-Your-First-Hudi-Lakehouse-with-AWS-Glue-and-AWS-S3/index.html +++ b/content/blog/2022/12/19/Build-Your-First-Hudi-Lakehouse-with-AWS-Glue-and-AWS-S3/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2022/12/29/Apache-Hudi-2022-A-Year-In-Review/index.html b/content/blog/2022/12/29/Apache-Hudi-2022-A-Year-In-Review/index.html index 5c722c679e88..e14ae35caca0 100644 --- a/content/blog/2022/12/29/Apache-Hudi-2022-A-Year-In-Review/index.html +++ b/content/blog/2022/12/29/Apache-Hudi-2022-A-Year-In-Review/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/01/11/Apache-Hudi-vs-Delta-Lake-vs-Apache-Iceberg-Lakehouse-Feature-Comparison/index.html b/content/blog/2023/01/11/Apache-Hudi-vs-Delta-Lake-vs-Apache-Iceberg-Lakehouse-Feature-Comparison/index.html index d22e32bc33bc..0a8bed2b007f 100644 --- a/content/blog/2023/01/11/Apache-Hudi-vs-Delta-Lake-vs-Apache-Iceberg-Lakehouse-Feature-Comparison/index.html +++ b/content/blog/2023/01/11/Apache-Hudi-vs-Delta-Lake-vs-Apache-Iceberg-Lakehouse-Feature-Comparison/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/01/27/Introducing-native-support-for-Apache-Hudi-Delta-Lake-Apache-Iceberg-on-AWS-Glue-for-Apache-Spark/index.html b/content/blog/2023/01/27/Introducing-native-support-for-Apache-Hudi-Delta-Lake-Apache-Iceberg-on-AWS-Glue-for-Apache-Spark/index.html index c3be5f7857e2..16fa2f0db7bb 100644 --- a/content/blog/2023/01/27/Introducing-native-support-for-Apache-Hudi-Delta-Lake-Apache-Iceberg-on-AWS-Glue-for-Apache-Spark/index.html +++ b/content/blog/2023/01/27/Introducing-native-support-for-Apache-Hudi-Delta-Lake-Apache-Iceberg-on-AWS-Glue-for-Apache-Spark/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/02/07/automate-schema-evolution-at-scale-with-apache-hudi-in-aws-glue/index.html b/content/blog/2023/02/07/automate-schema-evolution-at-scale-with-apache-hudi-in-aws-glue/index.html index a45517f8f4f7..134aeb419866 100644 --- a/content/blog/2023/02/07/automate-schema-evolution-at-scale-with-apache-hudi-in-aws-glue/index.html +++ b/content/blog/2023/02/07/automate-schema-evolution-at-scale-with-apache-hudi-in-aws-glue/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/02/12/table-service-deployment-models-in-apache-hudi/index.html b/content/blog/2023/02/12/table-service-deployment-models-in-apache-hudi/index.html index 27481a961848..71cc7180e6ef 100644 --- a/content/blog/2023/02/12/table-service-deployment-models-in-apache-hudi/index.html +++ b/content/blog/2023/02/12/table-service-deployment-models-in-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/02/19/bulk-insert-sort-modes-with-apache-hudi/index.html b/content/blog/2023/02/19/bulk-insert-sort-modes-with-apache-hudi/index.html index 8d7fde89a2e2..45675cc2689d 100644 --- a/content/blog/2023/02/19/bulk-insert-sort-modes-with-apache-hudi/index.html +++ b/content/blog/2023/02/19/bulk-insert-sort-modes-with-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/02/22/Getting-Started-Manage-your-Hudi-tables-with-the-admin-Hudi-CLI-tool/index.html b/content/blog/2023/02/22/Getting-Started-Manage-your-Hudi-tables-with-the-admin-Hudi-CLI-tool/index.html index 5b8eeed75033..acd11ae8c725 100644 --- a/content/blog/2023/02/22/Getting-Started-Manage-your-Hudi-tables-with-the-admin-Hudi-CLI-tool/index.html +++ b/content/blog/2023/02/22/Getting-Started-Manage-your-Hudi-tables-with-the-admin-Hudi-CLI-tool/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/03/16/Setting-Uber-Transactional-Data-Lake-in-Motion-with-Incremental-ETL-Using-Apache-Hudi/index.html b/content/blog/2023/03/16/Setting-Uber-Transactional-Data-Lake-in-Motion-with-Incremental-ETL-Using-Apache-Hudi/index.html index 11d976992061..d3c139e968d9 100644 --- a/content/blog/2023/03/16/Setting-Uber-Transactional-Data-Lake-in-Motion-with-Incremental-ETL-Using-Apache-Hudi/index.html +++ b/content/blog/2023/03/16/Setting-Uber-Transactional-Data-Lake-in-Motion-with-Incremental-ETL-Using-Apache-Hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/03/17/introduction-to-apache-hudi/index.html b/content/blog/2023/03/17/introduction-to-apache-hudi/index.html index 1f532ee7ca55..57663d26c389 100644 --- a/content/blog/2023/03/17/introduction-to-apache-hudi/index.html +++ b/content/blog/2023/03/17/introduction-to-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/03/20/Introducing-native-support-for-Apache Hudi-Delta-Lake-and-Apache-Iceberg-on-AWS-Glue-for-Apache-Spark-Part-2-AWS-Glue-Studio-Visual-Editor/index.html b/content/blog/2023/03/20/Introducing-native-support-for-Apache Hudi-Delta-Lake-and-Apache-Iceberg-on-AWS-Glue-for-Apache-Spark-Part-2-AWS-Glue-Studio-Visual-Editor/index.html index 899841cc68b6..049eed5912ab 100644 --- a/content/blog/2023/03/20/Introducing-native-support-for-Apache Hudi-Delta-Lake-and-Apache-Iceberg-on-AWS-Glue-for-Apache-Spark-Part-2-AWS-Glue-Studio-Visual-Editor/index.html +++ b/content/blog/2023/03/20/Introducing-native-support-for-Apache Hudi-Delta-Lake-and-Apache-Iceberg-on-AWS-Glue-for-Apache-Spark-Part-2-AWS-Glue-Studio-Visual-Editor/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/03/23/Spark-ETL-Chapter-8-with-Lakehouse-Apache-HUDI/index.html b/content/blog/2023/03/23/Spark-ETL-Chapter-8-with-Lakehouse-Apache-HUDI/index.html index b5c48db3eeba..21b664a5e099 100644 --- a/content/blog/2023/03/23/Spark-ETL-Chapter-8-with-Lakehouse-Apache-HUDI/index.html +++ b/content/blog/2023/03/23/Spark-ETL-Chapter-8-with-Lakehouse-Apache-HUDI/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/04/02/global-vs-non-global-index-in-apache-hudi/index.html b/content/blog/2023/04/02/global-vs-non-global-index-in-apache-hudi/index.html index 5ac571ace0e5..503bbfef818b 100644 --- a/content/blog/2023/04/02/global-vs-non-global-index-in-apache-hudi/index.html +++ b/content/blog/2023/04/02/global-vs-non-global-index-in-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/04/07/Speed-up-your-write-latencies-using-Bucket-Index-in-Apache-Hudi/index.html b/content/blog/2023/04/07/Speed-up-your-write-latencies-using-Bucket-Index-in-Apache-Hudi/index.html index 7dd3a64e19a6..7d012cca2845 100644 --- a/content/blog/2023/04/07/Speed-up-your-write-latencies-using-Bucket-Index-in-Apache-Hudi/index.html +++ b/content/blog/2023/04/07/Speed-up-your-write-latencies-using-Bucket-Index-in-Apache-Hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/04/18/getting-started-incrementally-process-data-with-apache-hudi/index.html b/content/blog/2023/04/18/getting-started-incrementally-process-data-with-apache-hudi/index.html index f9575741e910..2a22b8bf7654 100644 --- a/content/blog/2023/04/18/getting-started-incrementally-process-data-with-apache-hudi/index.html +++ b/content/blog/2023/04/18/getting-started-incrementally-process-data-with-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/04/26/the-lakehouse-trifecta/index.html b/content/blog/2023/04/26/the-lakehouse-trifecta/index.html index 18341cfbaf3a..b9bc967257c3 100644 --- a/content/blog/2023/04/26/the-lakehouse-trifecta/index.html +++ b/content/blog/2023/04/26/the-lakehouse-trifecta/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/04/29/can-you-concurrently-write-data-to-apache-hudi-w-o-any-lock-provider/index.html b/content/blog/2023/04/29/can-you-concurrently-write-data-to-apache-hudi-w-o-any-lock-provider/index.html index afb10570ad89..bd54b089bb0e 100644 --- a/content/blog/2023/04/29/can-you-concurrently-write-data-to-apache-hudi-w-o-any-lock-provider/index.html +++ b/content/blog/2023/04/29/can-you-concurrently-write-data-to-apache-hudi-w-o-any-lock-provider/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/05/02/intro-to-hudi-and-flink/index.html b/content/blog/2023/05/02/intro-to-hudi-and-flink/index.html index d18958b22002..c8b2e5d09832 100644 --- a/content/blog/2023/05/02/intro-to-hudi-and-flink/index.html +++ b/content/blog/2023/05/02/intro-to-hudi-and-flink/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/05/03/lakehouse-at-fortune-1-scale/index.html b/content/blog/2023/05/03/lakehouse-at-fortune-1-scale/index.html index ba20eb40a2ba..5ef72d85d859 100644 --- a/content/blog/2023/05/03/lakehouse-at-fortune-1-scale/index.html +++ b/content/blog/2023/05/03/lakehouse-at-fortune-1-scale/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/05/09/amazon-athena-apache-hudi/index.html b/content/blog/2023/05/09/amazon-athena-apache-hudi/index.html index a32833559c52..cf885b5ddf16 100644 --- a/content/blog/2023/05/09/amazon-athena-apache-hudi/index.html +++ b/content/blog/2023/05/09/amazon-athena-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/05/10/top-3-things-you-can-do-to-get-fast-upsert-performance-in-apache-hudi/index.html b/content/blog/2023/05/10/top-3-things-you-can-do-to-get-fast-upsert-performance-in-apache-hudi/index.html index aed8c9e68dd5..d2f043d5670e 100644 --- a/content/blog/2023/05/10/top-3-things-you-can-do-to-get-fast-upsert-performance-in-apache-hudi/index.html +++ b/content/blog/2023/05/10/top-3-things-you-can-do-to-get-fast-upsert-performance-in-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/05/12/ingesting-data-to-apache-hudi-using-spark-sql/index.html b/content/blog/2023/05/12/ingesting-data-to-apache-hudi-using-spark-sql/index.html index 7f7bc5cb99c9..ef3257d01c59 100644 --- a/content/blog/2023/05/12/ingesting-data-to-apache-hudi-using-spark-sql/index.html +++ b/content/blog/2023/05/12/ingesting-data-to-apache-hudi-using-spark-sql/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/05/16/how-zoom-implemented-streaming-log-ingestion-and-efficient-gdpr-deletes-using-apache-hudi-on-amazon-emr/index.html b/content/blog/2023/05/16/how-zoom-implemented-streaming-log-ingestion-and-efficient-gdpr-deletes-using-apache-hudi-on-amazon-emr/index.html index f7d51488beaf..0013fe5492a0 100644 --- a/content/blog/2023/05/16/how-zoom-implemented-streaming-log-ingestion-and-efficient-gdpr-deletes-using-apache-hudi-on-amazon-emr/index.html +++ b/content/blog/2023/05/16/how-zoom-implemented-streaming-log-ingestion-and-efficient-gdpr-deletes-using-apache-hudi-on-amazon-emr/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/05/19/hudi-metafields-demystified/index.html b/content/blog/2023/05/19/hudi-metafields-demystified/index.html index 5fcea448bace..46eb6db0d9fb 100644 --- a/content/blog/2023/05/19/hudi-metafields-demystified/index.html +++ b/content/blog/2023/05/19/hudi-metafields-demystified/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/05/29/different-query-types-with-apache-hudi/index.html b/content/blog/2023/05/29/different-query-types-with-apache-hudi/index.html index 05d476ca53fe..4eefab06272f 100644 --- a/content/blog/2023/05/29/different-query-types-with-apache-hudi/index.html +++ b/content/blog/2023/05/29/different-query-types-with-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/06/03/text-based-search-from-elastic-search-to-vector-search/index.html b/content/blog/2023/06/03/text-based-search-from-elastic-search-to-vector-search/index.html index e6800a451ae5..81a26e970f5c 100644 --- a/content/blog/2023/06/03/text-based-search-from-elastic-search-to-vector-search/index.html +++ b/content/blog/2023/06/03/text-based-search-from-elastic-search-to-vector-search/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/06/11/cleaner-and-archival-in-apache-hudi/index.html b/content/blog/2023/06/11/cleaner-and-archival-in-apache-hudi/index.html index e37144504045..6b4be442dd46 100644 --- a/content/blog/2023/06/11/cleaner-and-archival-in-apache-hudi/index.html +++ b/content/blog/2023/06/11/cleaner-and-archival-in-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/06/16/Exploring-New-Frontiers-How-Apache-Flink-Apache-Hudi-and-Presto-Power-New-Insights-at-Scale/index.html b/content/blog/2023/06/16/Exploring-New-Frontiers-How-Apache-Flink-Apache-Hudi-and-Presto-Power-New-Insights-at-Scale/index.html index 80401cde39a2..964b96583ada 100644 --- a/content/blog/2023/06/16/Exploring-New-Frontiers-How-Apache-Flink-Apache-Hudi-and-Presto-Power-New-Insights-at-Scale/index.html +++ b/content/blog/2023/06/16/Exploring-New-Frontiers-How-Apache-Flink-Apache-Hudi-and-Presto-Power-New-Insights-at-Scale/index.html @@ -19,7 +19,7 @@ - + diff --git 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a/content/blog/2023/06/24/multi-writer-support-in-apache-hudi/index.html +++ b/content/blog/2023/06/24/multi-writer-support-in-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/06/26/Unlimited-Big-Data-Exchange-A-Wonderful-Review-of-Apache-DolphinScheduler-and-Hudi-Hangzhou-Meetup/index.html b/content/blog/2023/06/26/Unlimited-Big-Data-Exchange-A-Wonderful-Review-of-Apache-DolphinScheduler-and-Hudi-Hangzhou-Meetup/index.html index fbc69d01394e..1536d8236a5a 100644 --- a/content/blog/2023/06/26/Unlimited-Big-Data-Exchange-A-Wonderful-Review-of-Apache-DolphinScheduler-and-Hudi-Hangzhou-Meetup/index.html +++ b/content/blog/2023/06/26/Unlimited-Big-Data-Exchange-A-Wonderful-Review-of-Apache-DolphinScheduler-and-Hudi-Hangzhou-Meetup/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/06/30/What-about-Apache-Hudi-Apache-Iceberg-and-Delta-Lake/index.html b/content/blog/2023/06/30/What-about-Apache-Hudi-Apache-Iceberg-and-Delta-Lake/index.html index 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b/content/blog/2023/07/02/Hudi-Best-Practices-Handling-Failed-Inserts-Upserts-with-Error-Tables/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/07/07/Skip-rocks-and-files-Turbocharge-Trino-queries-with-Hudi-multi-modal-indexing-subsystem/index.html b/content/blog/2023/07/07/Skip-rocks-and-files-Turbocharge-Trino-queries-with-Hudi-multi-modal-indexing-subsystem/index.html index e4b7b57217d5..85462dd2a1bb 100644 --- a/content/blog/2023/07/07/Skip-rocks-and-files-Turbocharge-Trino-queries-with-Hudi-multi-modal-indexing-subsystem/index.html +++ b/content/blog/2023/07/07/Skip-rocks-and-files-Turbocharge-Trino-queries-with-Hudi-multi-modal-indexing-subsystem/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/07/08/Quickly-start-using-Apache-Hudi-on-AWS-EMR/index.html b/content/blog/2023/07/08/Quickly-start-using-Apache-Hudi-on-AWS-EMR/index.html index 4f32ea53ad85..a42683520d30 100644 --- 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a/content/blog/2023/07/20/Backfilling-Apache-Hudi-Tables-in-Production-Techniques-and-Approaches-Using-AWS-Glue-by-Job-Target-LLC/index.html +++ b/content/blog/2023/07/20/Backfilling-Apache-Hudi-Tables-in-Production-Techniques-and-Approaches-Using-AWS-Glue-by-Job-Target-LLC/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/07/21/AWS-Glue-Crawlers-now-supports-Apache-Hudi-Tables/index.html b/content/blog/2023/07/21/AWS-Glue-Crawlers-now-supports-Apache-Hudi-Tables/index.html index 9edbc4ac271c..71bfdcd3f1e0 100644 --- a/content/blog/2023/07/21/AWS-Glue-Crawlers-now-supports-Apache-Hudi-Tables/index.html +++ b/content/blog/2023/07/21/AWS-Glue-Crawlers-now-supports-Apache-Hudi-Tables/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/07/27/Apache-Hudi-Revolutionizing-Big-Data-Management-for-Real-Time-Analytics/index.html b/content/blog/2023/07/27/Apache-Hudi-Revolutionizing-Big-Data-Management-for-Real-Time-Analytics/index.html index 74e36867bcff..93fac8907cae 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a/content/blog/2023/08/31/Incremental-Queries-with-Apache-Hudi-and-Apache-Flink/index.html +++ b/content/blog/2023/08/31/Incremental-Queries-with-Apache-Hudi-and-Apache-Flink/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/09/06/Apache-Hudi-From-Zero-To-One-blog-2/index.html b/content/blog/2023/09/06/Apache-Hudi-From-Zero-To-One-blog-2/index.html index 5c960b8e8970..41e64ed11b55 100644 --- a/content/blog/2023/09/06/Apache-Hudi-From-Zero-To-One-blog-2/index.html +++ b/content/blog/2023/09/06/Apache-Hudi-From-Zero-To-One-blog-2/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2023/09/06/Lakehouse-or-Warehouse-Part-1-of-2/index.html b/content/blog/2023/09/06/Lakehouse-or-Warehouse-Part-1-of-2/index.html index 5f3c933d5fb8..3a85963a69ae 100644 --- a/content/blog/2023/09/06/Lakehouse-or-Warehouse-Part-1-of-2/index.html +++ b/content/blog/2023/09/06/Lakehouse-or-Warehouse-Part-1-of-2/index.html @@ -19,7 +19,7 @@ - + diff --git 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a/content/blog/2024/02/06/Building-an-Open-Source-Data-Lake-House-with-Hudi-Postgres-Hive-Metastore-Minio-and-StarRocks/index.html b/content/blog/2024/02/06/Building-an-Open-Source-Data-Lake-House-with-Hudi-Postgres-Hive-Metastore-Minio-and-StarRocks/index.html index 418f37fb1e09..d3c199900385 100644 --- a/content/blog/2024/02/06/Building-an-Open-Source-Data-Lake-House-with-Hudi-Postgres-Hive-Metastore-Minio-and-StarRocks/index.html +++ b/content/blog/2024/02/06/Building-an-Open-Source-Data-Lake-House-with-Hudi-Postgres-Hive-Metastore-Minio-and-StarRocks/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/2024/02/06/Combine-Transactional-Integrity-and-Data-Lake-Operations-with-YugabyteDB-and-Apache-Hudi/index.html b/content/blog/2024/02/06/Combine-Transactional-Integrity-and-Data-Lake-Operations-with-YugabyteDB-and-Apache-Hudi/index.html index 4dd407480343..a1a40494b326 100644 --- 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a/content/blog/tags/robinhood/index.html +++ b/content/blog/tags/robinhood/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/rtinsights/index.html b/content/blog/tags/rtinsights/index.html index 9f0ed89d05d9..5a9046c92687 100644 --- a/content/blog/tags/rtinsights/index.html +++ b/content/blog/tags/rtinsights/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/scd-2/index.html b/content/blog/tags/scd-2/index.html index 0eccac146ad8..232c87fdc6a3 100644 --- a/content/blog/tags/scd-2/index.html +++ b/content/blog/tags/scd-2/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/schema-evolution/index.html b/content/blog/tags/schema-evolution/index.html index fb25f9c5e1ec..d6eb6f1a1312 100644 --- a/content/blog/tags/schema-evolution/index.html +++ b/content/blog/tags/schema-evolution/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/schema/index.html b/content/blog/tags/schema/index.html index b4332af9d556..b294a362e22e 100644 --- a/content/blog/tags/schema/index.html +++ b/content/blog/tags/schema/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/selectfrom/index.html b/content/blog/tags/selectfrom/index.html index a22a538c54e8..0544a68cc27e 100644 --- a/content/blog/tags/selectfrom/index.html +++ b/content/blog/tags/selectfrom/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/snapshot-exporter/index.html b/content/blog/tags/snapshot-exporter/index.html index 85a2b39870e7..d8d4bfedf0fb 100644 --- a/content/blog/tags/snapshot-exporter/index.html +++ b/content/blog/tags/snapshot-exporter/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/snapshot-query/index.html b/content/blog/tags/snapshot-query/index.html index b3d961fae31a..2579a33c2367 100644 --- a/content/blog/tags/snapshot-query/index.html +++ b/content/blog/tags/snapshot-query/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/space-filling-curves/index.html b/content/blog/tags/space-filling-curves/index.html index 3e53b89672a7..e235918783b0 100644 --- a/content/blog/tags/space-filling-curves/index.html +++ b/content/blog/tags/space-filling-curves/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/spark-sql/index.html b/content/blog/tags/spark-sql/index.html index 6223b6d3cc8c..2da9a63aae0f 100644 --- a/content/blog/tags/spark-sql/index.html +++ b/content/blog/tags/spark-sql/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/sql-transformer/index.html b/content/blog/tags/sql-transformer/index.html index 28e572ef2ed6..f61d913ff3a2 100644 --- a/content/blog/tags/sql-transformer/index.html +++ b/content/blog/tags/sql-transformer/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/starrocks/index.html b/content/blog/tags/starrocks/index.html index 5e4f268cadeb..3ef6311ee7fd 100644 --- a/content/blog/tags/starrocks/index.html +++ b/content/blog/tags/starrocks/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/storage-spec/index.html b/content/blog/tags/storage-spec/index.html index b04813ecd331..bcc1284e5090 100644 --- a/content/blog/tags/storage-spec/index.html +++ b/content/blog/tags/storage-spec/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/storage-types/index.html b/content/blog/tags/storage-types/index.html index d513e86015a5..62469ffacdbd 100644 --- a/content/blog/tags/storage-types/index.html +++ b/content/blog/tags/storage-types/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/storage/index.html b/content/blog/tags/storage/index.html index 5f04557c56bc..63ba52bfc094 100644 --- a/content/blog/tags/storage/index.html +++ b/content/blog/tags/storage/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/streaming-ingestion/index.html b/content/blog/tags/streaming-ingestion/index.html index 03c6de5c8390..0561b51ff141 100644 --- a/content/blog/tags/streaming-ingestion/index.html +++ b/content/blog/tags/streaming-ingestion/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/streaming/index.html b/content/blog/tags/streaming/index.html index 09f78de167a1..3ccf64fceee3 100644 --- a/content/blog/tags/streaming/index.html +++ b/content/blog/tags/streaming/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/streamlit/index.html b/content/blog/tags/streamlit/index.html index 129e415a309f..f3cd69ff18c4 100644 --- a/content/blog/tags/streamlit/index.html +++ b/content/blog/tags/streamlit/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/table-formats/index.html b/content/blog/tags/table-formats/index.html index 8c31debc1e38..86cd107d6be3 100644 --- a/content/blog/tags/table-formats/index.html +++ b/content/blog/tags/table-formats/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/table-service/index.html b/content/blog/tags/table-service/index.html index 316f0caf8b17..b1253509845a 100644 --- a/content/blog/tags/table-service/index.html +++ b/content/blog/tags/table-service/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/table-services/index.html b/content/blog/tags/table-services/index.html index 8435a15792c0..c348ebe03dec 100644 --- a/content/blog/tags/table-services/index.html +++ b/content/blog/tags/table-services/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/table-size-stats/index.html b/content/blog/tags/table-size-stats/index.html index d12611e75fcf..8f13a7ca384f 100644 --- a/content/blog/tags/table-size-stats/index.html +++ b/content/blog/tags/table-size-stats/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/techtarget/index.html b/content/blog/tags/techtarget/index.html index 3de24ec1de77..1f5307d7c3c0 100644 --- a/content/blog/tags/techtarget/index.html +++ b/content/blog/tags/techtarget/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/time-travel-query/index.html b/content/blog/tags/time-travel-query/index.html index e51ed3ba62a5..714cf39586de 100644 --- a/content/blog/tags/time-travel-query/index.html +++ b/content/blog/tags/time-travel-query/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/timeline-server/index.html b/content/blog/tags/timeline-server/index.html index 67a6a382e258..ec08df669a70 100644 --- a/content/blog/tags/timeline-server/index.html +++ b/content/blog/tags/timeline-server/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/timeline/index.html b/content/blog/tags/timeline/index.html index f21319fe84c0..d8c2a5a85fc2 100644 --- a/content/blog/tags/timeline/index.html +++ b/content/blog/tags/timeline/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/timestamp-as-of-query/index.html b/content/blog/tags/timestamp-as-of-query/index.html index 7037e610b8a0..5dbfce12e545 100644 --- a/content/blog/tags/timestamp-as-of-query/index.html +++ b/content/blog/tags/timestamp-as-of-query/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/timestamp-collision/index.html b/content/blog/tags/timestamp-collision/index.html index 1621cc7a6046..0054bce0fed4 100644 --- a/content/blog/tags/timestamp-collision/index.html +++ b/content/blog/tags/timestamp-collision/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/tla-specification/index.html b/content/blog/tags/tla-specification/index.html index cf22b2d39fb9..ff5e5c567c12 100644 --- a/content/blog/tags/tla-specification/index.html +++ b/content/blog/tags/tla-specification/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/towardsdatascience/index.html b/content/blog/tags/towardsdatascience/index.html index a719a8076056..dc4194673bae 100644 --- a/content/blog/tags/towardsdatascience/index.html +++ b/content/blog/tags/towardsdatascience/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/transactions/index.html b/content/blog/tags/transactions/index.html index 8db62b4c5320..4d92299d873b 100644 --- a/content/blog/tags/transactions/index.html +++ b/content/blog/tags/transactions/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/trino/index.html b/content/blog/tags/trino/index.html index 843dfe78b1e6..e3ef7a8450e2 100644 --- a/content/blog/tags/trino/index.html +++ b/content/blog/tags/trino/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/uber/index.html b/content/blog/tags/uber/index.html index 693453ed0448..5674c4746bb5 100644 --- a/content/blog/tags/uber/index.html +++ b/content/blog/tags/uber/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/upsert/index.html b/content/blog/tags/upsert/index.html index e14f2c420724..3b1761f10eb1 100644 --- a/content/blog/tags/upsert/index.html +++ b/content/blog/tags/upsert/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/upserts/index.html b/content/blog/tags/upserts/index.html index 91e0257859d4..879d629049ae 100644 --- a/content/blog/tags/upserts/index.html +++ b/content/blog/tags/upserts/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/upstox-engineering/index.html b/content/blog/tags/upstox-engineering/index.html index 7ba42c6a71e2..b75dcb212606 100644 --- a/content/blog/tags/upstox-engineering/index.html +++ b/content/blog/tags/upstox-engineering/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/use-case/index.html b/content/blog/tags/use-case/index.html index dc17fc4f35e2..036ff6175c58 100644 --- a/content/blog/tags/use-case/index.html +++ b/content/blog/tags/use-case/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/use-case/page/2/index.html b/content/blog/tags/use-case/page/2/index.html index 3297e3e14902..32d1a8a8274b 100644 --- a/content/blog/tags/use-case/page/2/index.html +++ b/content/blog/tags/use-case/page/2/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/use-case/page/3/index.html b/content/blog/tags/use-case/page/3/index.html index 43becdec86fe..2816e8f02f37 100644 --- a/content/blog/tags/use-case/page/3/index.html +++ b/content/blog/tags/use-case/page/3/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/vector-search/index.html b/content/blog/tags/vector-search/index.html index a3ae78a54592..afd137cf92e6 100644 --- a/content/blog/tags/vector-search/index.html +++ b/content/blog/tags/vector-search/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/venturebeat/index.html b/content/blog/tags/venturebeat/index.html index dff59dde9231..dcdc8cea6f42 100644 --- a/content/blog/tags/venturebeat/index.html +++ b/content/blog/tags/venturebeat/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/walmartglobaltech/index.html b/content/blog/tags/walmartglobaltech/index.html index bc33d5a700f5..e55be98079a1 100644 --- a/content/blog/tags/walmartglobaltech/index.html +++ b/content/blog/tags/walmartglobaltech/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/writes/index.html b/content/blog/tags/writes/index.html index e9163435226f..169dce9da956 100644 --- a/content/blog/tags/writes/index.html +++ b/content/blog/tags/writes/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/xenonstack/index.html b/content/blog/tags/xenonstack/index.html index c1371303128f..6ede002b877b 100644 --- a/content/blog/tags/xenonstack/index.html +++ b/content/blog/tags/xenonstack/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/yahoo/index.html b/content/blog/tags/yahoo/index.html index d035a83bae08..53d720a71b1b 100644 --- a/content/blog/tags/yahoo/index.html +++ b/content/blog/tags/yahoo/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/blog/tags/yugabyte/index.html b/content/blog/tags/yugabyte/index.html index 6cded0a012fa..58e05b9586f8 100644 --- a/content/blog/tags/yugabyte/index.html +++ b/content/blog/tags/yugabyte/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/404.html b/content/cn/404.html index 9f254c2a155c..cd9a5dbf0eba 100644 --- a/content/cn/404.html +++ b/content/cn/404.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/404/index.html b/content/cn/404/index.html index c9fe30b5b7dc..3d2e1f1dc6a6 100644 --- a/content/cn/404/index.html +++ b/content/cn/404/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/assets/js/2dada088.2f23ddfc.js b/content/cn/assets/js/2dada088.2f23ddfc.js deleted file mode 100644 index c98eae6664ab..000000000000 --- a/content/cn/assets/js/2dada088.2f23ddfc.js +++ /dev/null @@ -1 +0,0 @@ -"use strict";(self.webpackChunkhudi=self.webpackChunkhudi||[]).push([[72421],{98478:(e,i,a)=>{a.r(i),a.d(i,{assets:()=>d,contentTitle:()=>r,default:()=>c,frontMatter:()=>s,metadata:()=>o,toc:()=>l});var t=a(74848),n=a(28453);const s={title:"Powered By",keywords:["hudi","powered-by"],last_modified_at:new Date("2019-12-31T19:59:57.000Z")},r="Who's Using",o={type:"mdx",permalink:"/cn/powered-by",source:"@site/src/pages/powered-by.md",title:"Powered By",description:"Apache Hudi is a fast growing diverse 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Based on the Hadoop ecosystem, we built a new generation of big data platform based on Apache Hudi, which provides record-level updates/deletes as well as streaming and batch integrated data processing."]}),"\n",(0,t.jsx)(i.h3,{id:"disney-hotstar",children:"Disney+ Hotstar"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://youtu.be/ZamXiT9aqs8",children:"Disney shared"})," how they migrated CDC data to Apache Hudi to power a real-time ads platform for their streaming service."]}),"\n",(0,t.jsx)(i.h3,{id:"emis-health",children:"EMIS Health"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.emishealth.com/",children:"EMIS Health"})," is the largest provider of Primary Care IT software in the UK with datasets including more than 500Bn healthcare records. HUDI is used to manage their analytics dataset in production and keeping them up-to-date with their upstream source. Presto is being used to query the data written in HUDI format."]}),"\n",(0,t.jsx)(i.h3,{id:"forethought-ai",children:"Forethought AI"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://forethought.ai/",children:"Forethought AI"})," is the Leading Generative AI for Customer Support Automation. It unlocks efficiency with the generative AI automation platform that lowers support costs while providing top-tier service in every customer interaction."]}),"\n",(0,t.jsx)(i.h3,{id:"funding-circle",children:"Funding Circle"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.fundingcircle.com/us/",children:"Funding Circle"})," helps people invest in equipment or inventory, consolidate debt, grow their business, or pay business expenses by providing loans."]}),"\n",(0,t.jsx)(i.h3,{id:"ge-aviation",children:"GE Aviation"}),"\n",(0,t.jsx)(i.p,{children:(0,t.jsx)(i.a,{href:"https://aws.amazon.com/blogs/big-data/how-ge-aviation-built-cloud-native-data-pipelines-at-enterprise-scale-using-the-aws-platform/",children:"GE Aviation built cloud-native data pipelines at enterprise scale using Apache Hudi in AWS platform"})}),"\n",(0,t.jsx)(i.h3,{id:"grofers",children:"Grofers"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://grofers.com",children:"Grofers"})," is a grocery delivery provider operating across APAC region. Grofers has ",(0,t.jsx)(i.a,{href:"https://lambda.grofers.com/origins-of-data-lake-at-grofers-6c011f94b86c",children:"integrated hudi"})," in its central pipelines for replicating backend database CDC into the warehouse."]}),"\n",(0,t.jsx)(i.h3,{id:"h3c-digital-platform",children:"H3C Digital Platform"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"http://www.h3c.com/",children:"H3C digital platform"})," provides the whole process capability of data collection, storage, calculation and governance, and enables the construction of data center and data governance ability for medical, smart park, smart city and other industries;\nApache Hudi is integrated in the digital platform to meet the real-time update needs of massive data"]}),"\n",(0,t.jsx)(i.h3,{id:"halodoc",children:"Halodoc"}),"\n",(0,t.jsx)(i.p,{children:(0,t.jsx)(i.a,{href:"https://blogs.halodoc.io/lake-house-architecture-halodoc-data-platform-2-0/",children:"Lake House Architecture at Halodoc: Data Platform 2.0"})}),"\n",(0,t.jsx)(i.h3,{id:"jobtarget",children:"Jobtarget"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.jobtarget.com/",children:"Jobtarget"})," is a company dedicated to helping job seekers and employers connect. This focus has allowed us to earn the opportunity to serve thousands of companies and millions of job seekers each month."]}),"\n",(0,t.jsx)(i.h3,{id:"kyligence",children:"Kyligence"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://kyligence.io/zh/",children:"Kyligence"})," is the leading Big Data analytics platform company. We\u2019ve built end to end solutions for various Global Fortune 500 companies in US and China. We adopted Apache Hudi in our Cloud solution on AWS in 2019. With the help of Hudi, we are able to process upserts and deletes easily and we use incremental views to build efficient data pipelines in AWS. The Hudi datasets can also be integrated to Kyligence Cloud directly for high concurrent OLAP access."]}),"\n",(0,t.jsx)(i.h3,{id:"lingyue-digital-corporation",children:"Lingyue-digital Corporation"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.lingyue-digital.com/",children:"Lingyue-digital Corporation"})," belongs to BMW Group. Apache Hudi is used to perform ingest MySQL and PostgreSQL change data capture. We build up upsert scenarios on Hadoop and spark."]}),"\n",(0,t.jsx)(i.h3,{id:"logical-clocks",children:"Logical Clocks"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.logicalclocks.com/blog/introducing-the-hopsworks-1-x-series",children:"Hopsworks 1.x series"})," supports Apache Hudi feature groups, to enable upserts and time travel."]}),"\n",(0,t.jsx)(i.h3,{id:"navi",children:"Navi"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://navi.com/",children:"Navi"}),", one of India\u2019s fastest-growing financial service providers, offers Personal & Home Loans, UPI, Insurance, Mutual Funds, and Gold. Powered by Apache Hudi, our Data Platform tech stack has been enhanced to enable near-real-time data ingestion, driving AI/ML initiatives and critical business decisions to create exceptional customer experiences."]}),"\n",(0,t.jsx)(i.h3,{id:"nerdwallet",children:"NerdWallet"}),"\n",(0,t.jsx)(i.p,{children:(0,t.jsx)(i.a,{href:"https://aws.amazon.com/blogs/big-data/how-nerdwallet-uses-aws-and-apache-hudi-to-build-a-serverless-real-time-analytics-platform/",children:"NerdWallet uses AWS and Apache Hudi to build a serverless, real-time analytics platform"})}),"\n",(0,t.jsx)(i.h3,{id:"notion",children:"Notion"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.notion.so/",children:"Notion"})," is the connected workspace where modern teams create and share docs, take notes, manage their projects and time, and organize knowledge \u2014 with AI integrated throughout. Notion uses Apache Hudi to power their core analytics datasets and AI features."]}),"\n",(0,t.jsx)(i.h3,{id:"penn-interactive",children:"Penn Interactive"}),"\n",(0,t.jsxs)(i.p,{children:["The interactive arm of ",(0,t.jsx)(i.a,{href:"https://www.pennentertainment.com/",children:"Penn Entertainment"}),", encompassing Penn Interactive and theScore, is a major player in online and retail sports betting markets in the U.S. and Canada, as well as the sports media sector.Apache Hudi's efficient processing helps them to keep Spark resources reasonable while running hundreds of streaming jobs 24/7."]}),"\n",(0,t.jsx)(i.h3,{id:"robinhood",children:"Robinhood"}),"\n",(0,t.jsx)(i.p,{children:(0,t.jsx)(i.a,{href:"https://www.slideshare.net/BalajiVaradarajan13/rds-data-lake-robinhood",children:"Rds data lake at Robinhood using Apache Hudi"})}),"\n",(0,t.jsx)(i.h3,{id:"sf-express",children:"SF-Express"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.sf-express.com/cn/sc/",children:"SF-Express"})," is the leading logistics service provider in China. HUDI is used to build a real-time data warehouse, providing real-time computing solutions with higher efficiency and lower cost for our business."]}),"\n",(0,t.jsx)(i.h3,{id:"tathastuai",children:"Tathastu.ai"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.tathastu.ai",children:"Tathastu.ai"})," offers the largest AI/ML playground of consumer data for data scientists, AI experts and technologists to build upon. They have built a CDC pipeline using Apache Hudi and Debezium. Data from Hudi datasets is being queried using Hive, Presto and Spark."]}),"\n",(0,t.jsx)(i.h3,{id:"tencent",children:"Tencent"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://intl.cloud.tencent.com/product/emr",children:"EMR from Tencent"})," Cloud has integrated Hudi as one of its BigData components ",(0,t.jsx)(i.a,{href:"https://intl.cloud.tencent.com/document/product/1026/35587",children:"since V2.2.0"}),". Using Hudi, the end-users can handle either read-heavy or write-heavy use cases, and Hudi will manage the underlying data stored on HDFS/COS/CHDFS using Apache Parquet and Apache Avro."]}),"\n",(0,t.jsx)(i.h3,{id:"uber",children:"Uber"}),"\n",(0,t.jsxs)(i.p,{children:["Apache Hudi was originally developed at ",(0,t.jsx)(i.a,{href:"https://uber.com",children:"Uber"}),", to achieve ",(0,t.jsx)(i.a,{href:"http://www.slideshare.net/vinothchandar/hadoop-strata-talk-uber-your-hadoop-has-arrived/32",children:"low latency database ingestion, with high efficiency"}),".\nIt has been in production since Aug 2016, powering the massive ",(0,t.jsx)(i.a,{href:"https://eng.uber.com/uber-big-data-platform/",children:"100PB data lake"}),", including highly business critical tables like core trips,riders,partners. It also\npowers several incremental Hive ETL pipelines and being currently integrated into Uber's data dispersal system."]}),"\n",(0,t.jsx)(i.h3,{id:"udemy",children:"Udemy"}),"\n",(0,t.jsxs)(i.p,{children:["At ",(0,t.jsx)(i.a,{href:"https://www.udemy.com/",children:"Udemy"}),", Apache Hudi on AWS EMR is used to perform ingest MySQL change data capture."]}),"\n",(0,t.jsx)(i.h3,{id:"walmart",children:"Walmart"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://searchdatamanagement.techtarget.com/feature/Hudi-powering-data-lake-efforts-at-Walmart-and-Disney-Hotstar",children:"Walmart"}),"\nchose Apache Hudi to manage their data lake of store transactions."]}),"\n",(0,t.jsx)(i.h3,{id:"yieldsio",children:"Yields.io"}),"\n",(0,t.jsxs)(i.p,{children:["Yields.io is the first FinTech platform that uses AI for automated model validation and real-time monitoring on an enterprise-wide scale. Their ",(0,t.jsx)(i.a,{href:"https://www.yields.io/Blog/Apache-Hudi-at-Yields",children:"data lake"})," is managed by Hudi. They are also actively building their infrastructure for incremental, cross language/platform machine learning using Hudi."]}),"\n",(0,t.jsx)(i.h3,{id:"yotpo",children:"Yotpo"}),"\n",(0,t.jsxs)(i.p,{children:["Using Hudi at Yotpo for several usages. Firstly, integrated Hudi as a writer in their open source ETL framework, ",(0,t.jsx)(i.a,{href:"https://github.com/YotpoLtd/metorikku",children:"Metorikku"})," and using as an output writer for a CDC pipeline, with events that are being generated from a database binlog streams to Kafka and then are written to S3."]}),"\n",(0,t.jsx)(i.h3,{id:"zendesk",children:"Zendesk"}),"\n",(0,t.jsxs)(i.p,{children:["At ",(0,t.jsx)(i.a,{href:"https://www.zendesk.com/",children:"Zendesk"}),", Apache Hudi is adopted for building Data Lake on AWS."]}),"\n",(0,t.jsx)(i.h3,{id:"zto-express",children:"ZTO Express"}),"\n",(0,t.jsxs)(i.p,{children:[(0,t.jsx)(i.a,{href:"https://www.zto.com/",children:"ZTO Express"})," is a large group company integrating express delivery, logistics and other businesses.\nZTO uses Apache Hudi to build a technical architecture integrating lakes and warehouses. As the core of this architecture, Hudi has helped ZTO realize the quasi-real-time update and analysis capabilities of massive data."]})]})}function c(e={}){const{wrapper:i}={...(0,n.R)(),...e.components};return i?(0,t.jsx)(i,{...e,children:(0,t.jsx)(h,{...e})}):h(e)}},28453:(e,i,a)=>{a.d(i,{R:()=>r,x:()=>o});var t=a(96540);const n={},s=t.createContext(n);function r(e){const i=t.useContext(s);return t.useMemo((function(){return"function"==typeof e?e(i):{...i,...e}}),[i,e])}function o(e){let i;return i=e.disableParentContext?"function"==typeof e.components?e.components(n):e.components||n:r(e.components),t.createElement(s.Provider,{value:i},e.children)}}}]); \ No newline at end of file diff --git a/content/cn/assets/js/2dada088.4a68a53b.js b/content/cn/assets/js/2dada088.4a68a53b.js new file mode 100644 index 000000000000..3bd352a99e23 --- /dev/null +++ b/content/cn/assets/js/2dada088.4a68a53b.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkhudi=self.webpackChunkhudi||[]).push([[72421],{98478:(e,a,i)=>{i.r(a),i.d(a,{assets:()=>d,contentTitle:()=>r,default:()=>c,frontMatter:()=>s,metadata:()=>o,toc:()=>l});var t=i(74848),n=i(28453);const s={title:"Powered By",keywords:["hudi","powered-by"],last_modified_at:new Date("2019-12-31T19:59:57.000Z")},r="Who's Using",o={type:"mdx",permalink:"/cn/powered-by",source:"@site/src/pages/powered-by.md",title:"Powered By",description:"Apache Hudi is a fast growing diverse community",frontMatter:{title:"Powered By",keywords:["hudi","powered-by"],last_modified_at:"2019-12-31T19:59:57.000Z"},unlisted:!1},d={},l=[{value:"37 Interactive Entertainment",id:"37-interactive-entertainment",level:3},{value:"Alibaba Cloud",id:"alibaba-cloud",level:3},{value:"Amazon",id:"amazon",level:3},{value:"Amazon Web Services",id:"amazon-web-services",level:3},{value:"Applied Intuition",id:"applied-intuition",level:3},{value:"ByteDance",id:"bytedance",level:3},{value:"Clinbrain",id:"clinbrain",level:3},{value:"DiDi",id:"didi",level:3},{value:"Disney+ Hotstar",id:"disney-hotstar",level:3},{value:"EMIS Health",id:"emis-health",level:3},{value:"Forethought AI",id:"forethought-ai",level:3},{value:"Funding Circle",id:"funding-circle",level:3},{value:"GE Aviation",id:"ge-aviation",level:3},{value:"Grofers",id:"grofers",level:3},{value:"H3C Digital Platform",id:"h3c-digital-platform",level:3},{value:"Halodoc",id:"halodoc",level:3},{value:"Jobtarget",id:"jobtarget",level:3},{value:"Kyligence",id:"kyligence",level:3},{value:"Kuaishou",id:"kuaishou",level:3},{value:"Lingyue-digital Corporation",id:"lingyue-digital-corporation",level:3},{value:"Logical Clocks",id:"logical-clocks",level:3},{value:"Navi",id:"navi",level:3},{value:"NerdWallet",id:"nerdwallet",level:3},{value:"Notion",id:"notion",level:3},{value:"Penn Interactive",id:"penn-interactive",level:3},{value:"Robinhood",id:"robinhood",level:3},{value:"SF-Express",id:"sf-express",level:3},{value:"Tathastu.ai",id:"tathastuai",level:3},{value:"Tencent",id:"tencent",level:3},{value:"Uber",id:"uber",level:3},{value:"Udemy",id:"udemy",level:3},{value:"Walmart",id:"walmart",level:3},{value:"Yields.io",id:"yieldsio",level:3},{value:"Yotpo",id:"yotpo",level:3},{value:"Zendesk",id:"zendesk",level:3},{value:"ZTO Express",id:"zto-express",level:3}];function h(e){const a={a:"a",h1:"h1",h3:"h3",header:"header",p:"p",...(0,n.R)(),...e.components};return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(a.header,{children:(0,t.jsx)(a.h1,{id:"whos-using",children:"Who's Using"})}),"\n",(0,t.jsxs)(a.p,{children:["Apache Hudi is a ",(0,t.jsx)(a.a,{href:"https://hudi.apache.org/blog/2022/01/06/apache-hudi-2021-a-year-in-review",children:"fast growing diverse community"}),"\nof people and organizations from all around the globe. The following is a small sample of companies that have adopted or\ncontributed to the Apache Hudi community! ",(0,t.jsx)(a.a,{href:"https://join.slack.com/t/apache-hudi/shared_invite/zt-2ggm1fub8-_yt4Reu9djwqqVRFC7X49g",children:"Join us on slack"}),",\nor come to one of our ",(0,t.jsx)(a.a,{href:"https://hudi.apache.org/community/syncs",children:"virtual community events"}),"."]}),"\n",(0,t.jsx)(a.h3,{id:"37-interactive-entertainment",children:"37 Interactive Entertainment"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.37wan.net/",children:"37 Interactive Entertainment"})," is a global Top20 listed game company, and a leading company on A-shares market of China.\nApache Hudi is integrated into our Data Middle Platform offering real-time data warehouse and solving the problem of frequent changes of data.\nMeanwhile, we build a set of data access standards based on Hudi, which provides a guarantee for massive data queries in game operation scenarios."]}),"\n",(0,t.jsx)(a.h3,{id:"alibaba-cloud",children:"Alibaba Cloud"}),"\n",(0,t.jsxs)(a.p,{children:["Alibaba Cloud provides cloud computing services to online businesses and Alibaba's own e-commerce ecosystem, Apache Hudi is integrated into Alibaba Cloud ",(0,t.jsx)(a.a,{href:"https://www.alibabacloud.com/help/product/70174.htm",children:"Data Lake Analytics"}),"\noffering real-time analysis on hudi dataset."]}),"\n",(0,t.jsx)(a.h3,{id:"amazon",children:"Amazon"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://aws.amazon.com/blogs/big-data/how-amazon-transportation-service-enabled-near-real-time-event-analytics-at-petabyte-scale-using-aws-glue-with-apache-hudi/",children:"Amazon Transportation service"}),"\nuses Apache Hudi for the backbone of their package delivery system, powering petabyte-scale near real time analytics."]}),"\n",(0,t.jsx)(a.h3,{id:"amazon-web-services",children:"Amazon Web Services"}),"\n",(0,t.jsxs)(a.p,{children:["Amazon Web Services is the World's leading cloud services provider. Apache Hudi is ",(0,t.jsx)(a.a,{href:"https://aws.amazon.com/emr/features/hudi/",children:"pre-installed"})," with the AWS Elastic Map Reduce\noffering, providing means for AWS users to perform record-level updates/deletes and manage storage efficiently."]}),"\n",(0,t.jsx)(a.h3,{id:"applied-intuition",children:"Applied Intuition"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.appliedintuition.com/",children:"Applied Intuition"})," accelerates the world\u2019s adoption of safe and intelligent machines. Using Hudi, Applied supports querying across millions of simulations and hours of drive data for their customers. Its table features drastically improve querying performance while maintaining near real-time freshness."]}),"\n",(0,t.jsx)(a.h3,{id:"bytedance",children:"ByteDance"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://hudi.apache.org/blog/2021/09/01/building-eb-level-data-lake-using-hudi-at-bytedance/",children:"ByteDance"}),"\nuses Apache Hudi to power their Exabyte scale TikTok #ForYouPage realtime recommendation engine."]}),"\n",(0,t.jsx)(a.h3,{id:"clinbrain",children:"Clinbrain"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.clinbrain.com/",children:"Clinbrain"})," is the leader of big data platform and usage in medical industry. We have built 200 medical big data centers by integrating Hudi Data Lake solution in numerous hospitals. 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Grofers has ",(0,t.jsx)(a.a,{href:"https://lambda.grofers.com/origins-of-data-lake-at-grofers-6c011f94b86c",children:"integrated hudi"})," in its central pipelines for replicating backend database CDC into the warehouse."]}),"\n",(0,t.jsx)(a.h3,{id:"h3c-digital-platform",children:"H3C Digital Platform"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"http://www.h3c.com/",children:"H3C digital platform"})," provides the whole process capability of data collection, storage, calculation and governance, and enables the construction of data center and data governance ability for medical, smart park, smart city and other industries;\nApache Hudi is integrated in the digital platform to meet the real-time update needs of massive data"]}),"\n",(0,t.jsx)(a.h3,{id:"halodoc",children:"Halodoc"}),"\n",(0,t.jsx)(a.p,{children:(0,t.jsx)(a.a,{href:"https://blogs.halodoc.io/lake-house-architecture-halodoc-data-platform-2-0/",children:"Lake House Architecture at Halodoc: Data Platform 2.0"})}),"\n",(0,t.jsx)(a.h3,{id:"jobtarget",children:"Jobtarget"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.jobtarget.com/",children:"Jobtarget"})," is a company dedicated to helping job seekers and employers connect. This focus has allowed us to earn the opportunity to serve thousands of companies and millions of job seekers each month."]}),"\n",(0,t.jsx)(a.h3,{id:"kyligence",children:"Kyligence"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://kyligence.io/zh/",children:"Kyligence"})," is the leading Big Data analytics platform company. We\u2019ve built end to end solutions for various Global Fortune 500 companies in US and China. We adopted Apache Hudi in our Cloud solution on AWS in 2019. With the help of Hudi, we are able to process upserts and deletes easily and we use incremental views to build efficient data pipelines in AWS. The Hudi datasets can also be integrated to Kyligence Cloud directly for high concurrent OLAP access."]}),"\n",(0,t.jsx)(a.h3,{id:"kuaishou",children:"Kuaishou"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.kuaishou.com/en/",children:"Kuaishou"})," is a prominent Chinese giant in the content community and social platform. The company offers a diverse range of services, including live streaming, short videos, and e-commerce. At Kuaishou, both AI experts and BI technologists leverage Hudi to handle their online business cases. In AI scenarios, Hudi is used to build a unified batch-stream sample lake at the exabyte (EB) scale and end-to-end latency of 30 seconds. The sample lake supports both online and offline training. In BI scenarios, Hudi enhances the traditional HIVE data warehouse by enabling streaming ingestion into the lakehouse at the ODS layer. It efficiently processes append and upsert streams, while also supporting incremental updates across the DWD, DWS, and ADS layers. Currently, Hudi plays a key role in both BI and AI scenarios at Kuaishou."]}),"\n",(0,t.jsx)(a.h3,{id:"lingyue-digital-corporation",children:"Lingyue-digital Corporation"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.lingyue-digital.com/",children:"Lingyue-digital Corporation"})," belongs to BMW Group. Apache Hudi is used to perform ingest MySQL and PostgreSQL change data capture. We build up upsert scenarios on Hadoop and spark."]}),"\n",(0,t.jsx)(a.h3,{id:"logical-clocks",children:"Logical Clocks"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.logicalclocks.com/blog/introducing-the-hopsworks-1-x-series",children:"Hopsworks 1.x series"})," supports Apache Hudi feature groups, to enable upserts and time travel."]}),"\n",(0,t.jsx)(a.h3,{id:"navi",children:"Navi"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://navi.com/",children:"Navi"}),", one of India\u2019s fastest-growing financial service providers, offers Personal & Home Loans, UPI, Insurance, Mutual Funds, and Gold. Powered by Apache Hudi, our Data Platform tech stack has been enhanced to enable near-real-time data ingestion, driving AI/ML initiatives and critical business decisions to create exceptional customer experiences."]}),"\n",(0,t.jsx)(a.h3,{id:"nerdwallet",children:"NerdWallet"}),"\n",(0,t.jsx)(a.p,{children:(0,t.jsx)(a.a,{href:"https://aws.amazon.com/blogs/big-data/how-nerdwallet-uses-aws-and-apache-hudi-to-build-a-serverless-real-time-analytics-platform/",children:"NerdWallet uses AWS and Apache Hudi to build a serverless, real-time analytics platform"})}),"\n",(0,t.jsx)(a.h3,{id:"notion",children:"Notion"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.notion.so/",children:"Notion"})," is the connected workspace where modern teams create and share docs, take notes, manage their projects and time, and organize knowledge \u2014 with AI integrated throughout. Notion uses Apache Hudi to power their core analytics datasets and AI features."]}),"\n",(0,t.jsx)(a.h3,{id:"penn-interactive",children:"Penn Interactive"}),"\n",(0,t.jsxs)(a.p,{children:["The interactive arm of ",(0,t.jsx)(a.a,{href:"https://www.pennentertainment.com/",children:"Penn Entertainment"}),", encompassing Penn Interactive and theScore, is a major player in online and retail sports betting markets in the U.S. and Canada, as well as the sports media sector.Apache Hudi's efficient processing helps them to keep Spark resources reasonable while running hundreds of streaming jobs 24/7."]}),"\n",(0,t.jsx)(a.h3,{id:"robinhood",children:"Robinhood"}),"\n",(0,t.jsx)(a.p,{children:(0,t.jsx)(a.a,{href:"https://www.slideshare.net/BalajiVaradarajan13/rds-data-lake-robinhood",children:"Rds data lake at Robinhood using Apache Hudi"})}),"\n",(0,t.jsx)(a.h3,{id:"sf-express",children:"SF-Express"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.sf-express.com/cn/sc/",children:"SF-Express"})," is the leading logistics service provider in China. HUDI is used to build a real-time data warehouse, providing real-time computing solutions with higher efficiency and lower cost for our business."]}),"\n",(0,t.jsx)(a.h3,{id:"tathastuai",children:"Tathastu.ai"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.tathastu.ai",children:"Tathastu.ai"})," offers the largest AI/ML playground of consumer data for data scientists, AI experts and technologists to build upon. They have built a CDC pipeline using Apache Hudi and Debezium. Data from Hudi datasets is being queried using Hive, Presto and Spark."]}),"\n",(0,t.jsx)(a.h3,{id:"tencent",children:"Tencent"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://intl.cloud.tencent.com/product/emr",children:"EMR from Tencent"})," Cloud has integrated Hudi as one of its BigData components ",(0,t.jsx)(a.a,{href:"https://intl.cloud.tencent.com/document/product/1026/35587",children:"since V2.2.0"}),". Using Hudi, the end-users can handle either read-heavy or write-heavy use cases, and Hudi will manage the underlying data stored on HDFS/COS/CHDFS using Apache Parquet and Apache Avro."]}),"\n",(0,t.jsx)(a.h3,{id:"uber",children:"Uber"}),"\n",(0,t.jsxs)(a.p,{children:["Apache Hudi was originally developed at ",(0,t.jsx)(a.a,{href:"https://uber.com",children:"Uber"}),", to achieve ",(0,t.jsx)(a.a,{href:"http://www.slideshare.net/vinothchandar/hadoop-strata-talk-uber-your-hadoop-has-arrived/32",children:"low latency database ingestion, with high efficiency"}),".\nIt has been in production since Aug 2016, powering the massive ",(0,t.jsx)(a.a,{href:"https://eng.uber.com/uber-big-data-platform/",children:"100PB data lake"}),", including highly business critical tables like core trips,riders,partners. It also\npowers several incremental Hive ETL pipelines and being currently integrated into Uber's data dispersal system."]}),"\n",(0,t.jsx)(a.h3,{id:"udemy",children:"Udemy"}),"\n",(0,t.jsxs)(a.p,{children:["At ",(0,t.jsx)(a.a,{href:"https://www.udemy.com/",children:"Udemy"}),", Apache Hudi on AWS EMR is used to perform ingest MySQL change data capture."]}),"\n",(0,t.jsx)(a.h3,{id:"walmart",children:"Walmart"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://searchdatamanagement.techtarget.com/feature/Hudi-powering-data-lake-efforts-at-Walmart-and-Disney-Hotstar",children:"Walmart"}),"\nchose Apache Hudi to manage their data lake of store transactions."]}),"\n",(0,t.jsx)(a.h3,{id:"yieldsio",children:"Yields.io"}),"\n",(0,t.jsxs)(a.p,{children:["Yields.io is the first FinTech platform that uses AI for automated model validation and real-time monitoring on an enterprise-wide scale. Their ",(0,t.jsx)(a.a,{href:"https://www.yields.io/Blog/Apache-Hudi-at-Yields",children:"data lake"})," is managed by Hudi. They are also actively building their infrastructure for incremental, cross language/platform machine learning using Hudi."]}),"\n",(0,t.jsx)(a.h3,{id:"yotpo",children:"Yotpo"}),"\n",(0,t.jsxs)(a.p,{children:["Using Hudi at Yotpo for several usages. Firstly, integrated Hudi as a writer in their open source ETL framework, ",(0,t.jsx)(a.a,{href:"https://github.com/YotpoLtd/metorikku",children:"Metorikku"})," and using as an output writer for a CDC pipeline, with events that are being generated from a database binlog streams to Kafka and then are written to S3."]}),"\n",(0,t.jsx)(a.h3,{id:"zendesk",children:"Zendesk"}),"\n",(0,t.jsxs)(a.p,{children:["At ",(0,t.jsx)(a.a,{href:"https://www.zendesk.com/",children:"Zendesk"}),", Apache Hudi is adopted for building Data Lake on AWS."]}),"\n",(0,t.jsx)(a.h3,{id:"zto-express",children:"ZTO Express"}),"\n",(0,t.jsxs)(a.p,{children:[(0,t.jsx)(a.a,{href:"https://www.zto.com/",children:"ZTO Express"})," is a large group company integrating express delivery, logistics and other businesses.\nZTO uses Apache Hudi to build a technical architecture integrating lakes and warehouses. 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a/content/cn/blog/2023/06/11/cleaner-and-archival-in-apache-hudi/index.html +++ b/content/cn/blog/2023/06/11/cleaner-and-archival-in-apache-hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/06/16/Exploring-New-Frontiers-How-Apache-Flink-Apache-Hudi-and-Presto-Power-New-Insights-at-Scale/index.html b/content/cn/blog/2023/06/16/Exploring-New-Frontiers-How-Apache-Flink-Apache-Hudi-and-Presto-Power-New-Insights-at-Scale/index.html index 71f9ff1fe45b..a5d2048ebcd3 100644 --- a/content/cn/blog/2023/06/16/Exploring-New-Frontiers-How-Apache-Flink-Apache-Hudi-and-Presto-Power-New-Insights-at-Scale/index.html +++ b/content/cn/blog/2023/06/16/Exploring-New-Frontiers-How-Apache-Flink-Apache-Hudi-and-Presto-Power-New-Insights-at-Scale/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/06/20/How-to-query-data-in-Apache-Hudi-using-StarRocks/index.html b/content/cn/blog/2023/06/20/How-to-query-data-in-Apache-Hudi-using-StarRocks/index.html index 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b/content/cn/blog/2023/06/30/What-about-Apache-Hudi-Apache-Iceberg-and-Delta-Lake/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/07/01/monitoring-table-size-stats/index.html b/content/cn/blog/2023/07/01/monitoring-table-size-stats/index.html index 6ed2d135c310..fd94633f41d7 100644 --- a/content/cn/blog/2023/07/01/monitoring-table-size-stats/index.html +++ b/content/cn/blog/2023/07/01/monitoring-table-size-stats/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/07/02/Hudi-Best-Practices-Handling-Failed-Inserts-Upserts-with-Error-Tables/index.html b/content/cn/blog/2023/07/02/Hudi-Best-Practices-Handling-Failed-Inserts-Upserts-with-Error-Tables/index.html index 9f0c3cfe7195..cf93945ea708 100644 --- a/content/cn/blog/2023/07/02/Hudi-Best-Practices-Handling-Failed-Inserts-Upserts-with-Error-Tables/index.html +++ b/content/cn/blog/2023/07/02/Hudi-Best-Practices-Handling-Failed-Inserts-Upserts-with-Error-Tables/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/07/07/Skip-rocks-and-files-Turbocharge-Trino-queries-with-Hudi-multi-modal-indexing-subsystem/index.html b/content/cn/blog/2023/07/07/Skip-rocks-and-files-Turbocharge-Trino-queries-with-Hudi-multi-modal-indexing-subsystem/index.html index 01aadae99994..879173fcfbac 100644 --- a/content/cn/blog/2023/07/07/Skip-rocks-and-files-Turbocharge-Trino-queries-with-Hudi-multi-modal-indexing-subsystem/index.html +++ b/content/cn/blog/2023/07/07/Skip-rocks-and-files-Turbocharge-Trino-queries-with-Hudi-multi-modal-indexing-subsystem/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/07/08/Quickly-start-using-Apache-Hudi-on-AWS-EMR/index.html b/content/cn/blog/2023/07/08/Quickly-start-using-Apache-Hudi-on-AWS-EMR/index.html index e291b1e43d45..d10050275fc8 100644 --- a/content/cn/blog/2023/07/08/Quickly-start-using-Apache-Hudi-on-AWS-EMR/index.html +++ b/content/cn/blog/2023/07/08/Quickly-start-using-Apache-Hudi-on-AWS-EMR/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/07/09/Hoodie-Timeline-Foundational-pillar-for-ACID-transactions/index.html b/content/cn/blog/2023/07/09/Hoodie-Timeline-Foundational-pillar-for-ACID-transactions/index.html index 7e5e4288c630..5da1f8874907 100644 --- a/content/cn/blog/2023/07/09/Hoodie-Timeline-Foundational-pillar-for-ACID-transactions/index.html +++ b/content/cn/blog/2023/07/09/Hoodie-Timeline-Foundational-pillar-for-ACID-transactions/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/07/20/Backfilling-Apache-Hudi-Tables-in-Production-Techniques-and-Approaches-Using-AWS-Glue-by-Job-Target-LLC/index.html b/content/cn/blog/2023/07/20/Backfilling-Apache-Hudi-Tables-in-Production-Techniques-and-Approaches-Using-AWS-Glue-by-Job-Target-LLC/index.html index 15f8e6993484..ee86a8570699 100644 --- a/content/cn/blog/2023/07/20/Backfilling-Apache-Hudi-Tables-in-Production-Techniques-and-Approaches-Using-AWS-Glue-by-Job-Target-LLC/index.html +++ b/content/cn/blog/2023/07/20/Backfilling-Apache-Hudi-Tables-in-Production-Techniques-and-Approaches-Using-AWS-Glue-by-Job-Target-LLC/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/07/21/AWS-Glue-Crawlers-now-supports-Apache-Hudi-Tables/index.html b/content/cn/blog/2023/07/21/AWS-Glue-Crawlers-now-supports-Apache-Hudi-Tables/index.html index ca02b53c78bb..a679f6ba93fb 100644 --- a/content/cn/blog/2023/07/21/AWS-Glue-Crawlers-now-supports-Apache-Hudi-Tables/index.html +++ b/content/cn/blog/2023/07/21/AWS-Glue-Crawlers-now-supports-Apache-Hudi-Tables/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/07/27/Apache-Hudi-Revolutionizing-Big-Data-Management-for-Real-Time-Analytics/index.html b/content/cn/blog/2023/07/27/Apache-Hudi-Revolutionizing-Big-Data-Management-for-Real-Time-Analytics/index.html index 5f25deffc333..a9313e7e9316 100644 --- a/content/cn/blog/2023/07/27/Apache-Hudi-Revolutionizing-Big-Data-Management-for-Real-Time-Analytics/index.html +++ b/content/cn/blog/2023/07/27/Apache-Hudi-Revolutionizing-Big-Data-Management-for-Real-Time-Analytics/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/08/03/Apache-Hudi-on-AWS-Glue-A-Step-by-Step-Guide/index.html b/content/cn/blog/2023/08/03/Apache-Hudi-on-AWS-Glue-A-Step-by-Step-Guide/index.html index 585dbd82278f..10cbef364966 100644 --- a/content/cn/blog/2023/08/03/Apache-Hudi-on-AWS-Glue-A-Step-by-Step-Guide/index.html +++ b/content/cn/blog/2023/08/03/Apache-Hudi-on-AWS-Glue-A-Step-by-Step-Guide/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/08/03/Create-an-Apache-Hudi-based-near-real-time-transactional-data lake-using-AWS-DMS-Amazon-Kinesis-AWS-Glue-streaming-ETL-and-data-visualization-using-Amazon-QuickSight/index.html b/content/cn/blog/2023/08/03/Create-an-Apache-Hudi-based-near-real-time-transactional-data lake-using-AWS-DMS-Amazon-Kinesis-AWS-Glue-streaming-ETL-and-data-visualization-using-Amazon-QuickSight/index.html index c8e0bc24bbe3..19859f35df75 100644 --- a/content/cn/blog/2023/08/03/Create-an-Apache-Hudi-based-near-real-time-transactional-data lake-using-AWS-DMS-Amazon-Kinesis-AWS-Glue-streaming-ETL-and-data-visualization-using-Amazon-QuickSight/index.html +++ b/content/cn/blog/2023/08/03/Create-an-Apache-Hudi-based-near-real-time-transactional-data lake-using-AWS-DMS-Amazon-Kinesis-AWS-Glue-streaming-ETL-and-data-visualization-using-Amazon-QuickSight/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/08/03/Data-lake-Table-formats-Apache-Iceberg-vs-Apache-Hudi-vs-Delta-lake/index.html b/content/cn/blog/2023/08/03/Data-lake-Table-formats-Apache-Iceberg-vs-Apache-Hudi-vs-Delta-lake/index.html index b5d95205f160..0e0a09264e4b 100644 --- a/content/cn/blog/2023/08/03/Data-lake-Table-formats-Apache-Iceberg-vs-Apache-Hudi-vs-Delta-lake/index.html +++ b/content/cn/blog/2023/08/03/Data-lake-Table-formats-Apache-Iceberg-vs-Apache-Hudi-vs-Delta-lake/index.html @@ -19,7 +19,7 @@ - + diff --git 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a/content/cn/blog/2023/08/22/Exploring-various-storage-types-in-Apache-Hudi/index.html b/content/cn/blog/2023/08/22/Exploring-various-storage-types-in-Apache-Hudi/index.html index 90aa9ca106d2..91cce909ca29 100644 --- a/content/cn/blog/2023/08/22/Exploring-various-storage-types-in-Apache-Hudi/index.html +++ b/content/cn/blog/2023/08/22/Exploring-various-storage-types-in-Apache-Hudi/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/08/25/Delta-Hudi-Iceberg-Which-is-most-popular/index.html b/content/cn/blog/2023/08/25/Delta-Hudi-Iceberg-Which-is-most-popular/index.html index b20ed5d9d306..e8b0e49ee4e1 100644 --- a/content/cn/blog/2023/08/25/Delta-Hudi-Iceberg-Which-is-most-popular/index.html +++ b/content/cn/blog/2023/08/25/Delta-Hudi-Iceberg-Which-is-most-popular/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/08/28/Apache-Hudi-From-Zero-To-One/index.html b/content/cn/blog/2023/08/28/Apache-Hudi-From-Zero-To-One/index.html index 9e84256e049f..35b387acb689 100644 --- a/content/cn/blog/2023/08/28/Apache-Hudi-From-Zero-To-One/index.html +++ b/content/cn/blog/2023/08/28/Apache-Hudi-From-Zero-To-One/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/08/28/Delta-Hudi-Iceberg-A-Benchmark-Compilation/index.html b/content/cn/blog/2023/08/28/Delta-Hudi-Iceberg-A-Benchmark-Compilation/index.html index ef18f1183aae..366579512e79 100644 --- a/content/cn/blog/2023/08/28/Delta-Hudi-Iceberg-A-Benchmark-Compilation/index.html +++ b/content/cn/blog/2023/08/28/Delta-Hudi-Iceberg-A-Benchmark-Compilation/index.html @@ -19,7 +19,7 @@ - + diff --git a/content/cn/blog/2023/08/31/Incremental-Queries-with-Apache-Hudi-and-Apache-Flink/index.html b/content/cn/blog/2023/08/31/Incremental-Queries-with-Apache-Hudi-and-Apache-Flink/index.html index 81bf11fd210f..c15e5ed38e20 100644 --- a/content/cn/blog/2023/08/31/Incremental-Queries-with-Apache-Hudi-and-Apache-Flink/index.html +++ 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JobtargetJobtarget is a company dedicated to helping job seekers and employers connect. This focus has allowed us to earn the opportunity to serve thousands of companies and millions of job seekers each month.

Kyligence​

Kyligence is the leading Big Data analytics platform company. We’ve built end to end solutions for various Global Fortune 500 companies in US and China. We adopted Apache Hudi in our Cloud solution on AWS in 2019. With the help of Hudi, we are able to process upserts and deletes easily and we use incremental views to build efficient data pipelines in AWS. The Hudi datasets can also be integrated to Kyligence Cloud directly for high concurrent OLAP access.

+

Kuaishou​

+

Kuaishou is a prominent Chinese giant in the content community and social platform. The company offers a diverse range of services, including live streaming, short videos, and e-commerce. At Kuaishou, both AI experts and BI technologists leverage Hudi to handle their online business cases. In AI scenarios, Hudi is used to build a unified batch-stream sample lake at the exabyte (EB) scale and end-to-end latency of 30 seconds. The sample lake supports both online and offline training. In BI scenarios, Hudi enhances the traditional HIVE data warehouse by enabling streaming ingestion into the lakehouse at the ODS layer. It efficiently processes append and upsert streams, while also supporting incremental updates across the DWD, DWS, and ADS layers. Currently, Hudi plays a key role in both BI and AI scenarios at Kuaishou.

Lingyue-digital Corporation​

Lingyue-digital Corporation belongs to BMW Group. Apache Hudi is used to perform ingest MySQL and PostgreSQL change data capture. We build up upsert scenarios on Hadoop and spark.

Logical Clocks​

@@ -108,7 +110,7 @@

ZendeskZendesk, Apache Hudi is adopted for building Data Lake on AWS.

ZTO Express​

ZTO Express is a large group company integrating express delivery, logistics and other businesses. -ZTO uses Apache Hudi to build a technical architecture integrating lakes and warehouses. As the core of this architecture, Hudi has helped ZTO realize the quasi-real-time update and analysis capabilities of massive data.