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Apache Airflow is an open-source workflow orchestration platform with 39K+ GitHub stars for authoring, scheduling, and monitoring data pipelines as Python DAGs. Used by 80K+ organizations for ETL, ML training, and data transformation. Features dynamic pipeline generation, extensive operator library for AWS/GCP/Azure, task dependencies, retries, SLA monitoring, a rich web UI with Gantt charts, and pluggable executors from local to Kubernetes. The industry standard for pipeline orchestration.
Apache Airflow is the industry standard for workflow orchestration, defining complex data pipelines as DAGs in Python. 39K+ GitHub stars, 80K+ organizations, billions of tasks daily.
Pipelines as Python code provide full flexibility. Extensive operators connect to AWS, GCP, Azure, databases, and APIs.
Web UI shows real-time status, Gantt charts, and task logs. Executors scale from local to Kubernetes. Managed services include Cloud Composer, AWS MWAA, and Astronomer.
Free open-source / Managed services available
Python, Docker, Kubernetes, Cloud
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