ingestr is a CLI tool to copy data between any databases with a single command seamlessly.
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Updated
Oct 22, 2025 - Python
ingestr is a CLI tool to copy data between any databases with a single command seamlessly.
Python based Open Source ETL tools for file crawling, document processing (text extraction, OCR), content analysis (Entity Extraction & Named Entity Recognition) & data enrichment (annotation) pipelines & ingestor to Solr or Elastic search index & linked data graph database
From data to vector database effortlessly
AzLogDcrIngestPS - Unleashing the power of Log Ingestion API with Azure LogAnalytics custom table v2, Azure Data Collection Rules and Azure Data Ingestion Pipeline
Google Cloud Storage connector, pre-processor and model for predicting user search intent based on keywords
Google Analytics connector, pre-processor and model for predicting churning users for digital publishers.
Extract Transform and Load unstructured data into the Clarifai's AI platform
My experiments with Apache Spark for Humans ⭐
Multi-disease segmentation chest X-rays by YOLO and DenseNet121, CoAtNet models
Real-time flight data fetching, cleaning, and analytics API using FastAPI, Pandas, PostgreSQL, and Python.
A Question Answering(Q/A) Chatbot on Insurance Documents. Powered by Retrieval Augmented Generation(RAG), LlamaIndex and LangGraph. Inspired from my Upgrad_IIITB PG Course.
Sample Azure Data Factory pipeline for ingesting Data Packages directly from the Download API of the Ordnance Survey Data Hub into Azure Storage.
DataStax or Cassandra Ingest from Relational Databases with StreamSets
Data stack for WeLearn LPI projects. This pipeline can collect, vectorize and store data from various sources.
Created a data pipeline using sqoop to ingest data from sql server into the hive table and used hive for feature engineering and analysis.
Easily fetch free historical Binance Futures candlestick (OHLCV candle) data with this simple and powerful Python script. Download years of data (e.g., 2021–2025) for any symbol and interval — all without API keys or paid plans.
A Question Answering(Q/A) Chatbot on Insurance Documents. Powered by Retrieval Augmented Generation(RAG), LlamaIndex and LangChain. Inspired from my Upgrad_IIITB PG Course.
The multinational retail data contralisation project is a data warehousing project that focuses on ingesting data from disparate sources to create a centralised warehouse
A real-life end-to-end cloud sub-system scenario
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