Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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Updated
Mar 22, 2025 - Python
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Elyra extends JupyterLab with an AI centric approach.
A series of DAGs/Workflows to help maintain the operation of Airflow
An end-to-end GoodReads Data Pipeline for Building Data Lake, Data Warehouse and Analytics Platform.
Dynamically generate Apache Airflow DAGs from YAML configuration files
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
Run your dbt Core projects as Apache Airflow DAGs and Task Groups with a few lines of code
Helm Charts for the Astronomer Platform, Apache Airflow as a Service on Kubernetes
Airflow DAGs for exporting, loading, and parsing the Ethereum blockchain data. How to get any Ethereum smart contract into BigQuery https://towardsdatascience.com/how-to-get-any-ethereum-smart-contract-into-bigquery-in-8-mins-bab5db1fdeee
Apache Airflow - OpenApi Client for Python
Example DAGs using hooks and operators from Airflow Plugins
A plugin for Apache Airflow that exposes rest end points for the Command Line Interfaces
A Helm chart to install Apache Airflow on Kubernetes
A web frontend for scheduling Jupyter notebook reports
An end-to-end data engineering pipeline that orchestrates data ingestion, processing, and storage using Apache Airflow, Python, Apache Kafka, Apache Zookeeper, Apache Spark, and Cassandra. All components are containerized with Docker for easy deployment and scalability.
A process that runs in unison with Apache Airflow to control the Scheduler process to ensure High Availability
A CLI tool to streamline getting started with Apache Airflow™ and managing multiple Airflow projects
Apache Airflow in Docker Compose (for both versions 1.10.* and 2.*)
Distributed run of dbt models using Airflow
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