Apache Airflow
A workflow orchestrator for scheduling and monitoring data pipelines defined as code.
Overview
Apache Airflow schedules workflows written as Python DAGs. The scheduler tracks dependencies, workers execute tasks, and the web UI shows run history, logs, and retries.
Where it fits
- Building ETL and ELT pipelines
- Scheduling recurring data jobs
- Monitoring task dependencies and retries
Key capabilities
- Python-defined DAGs
- Scheduler and executors
- Web UI for runs and logs
- Operators and provider packages
Repository metadata
- Stars (snapshot)
- 47,371
- Main language
- Python
- License
- Apache-2.0
- Topics
- airflow, apache, apache-airflow, automation, dag, data-engineering, data-integration, data-orchestrator, data-pipelines, data-science, elt, etl, machine-learning, mlops, orchestration, python, scheduler, workflow, workflow-engine, workflow-orchestration
- Category
- Data & analytics
- Last push
- 2026-11-05T12:42:57Z
Repository description from GitHub metadata: Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Official links
- Official repository
- Read the README The README is linked, not copied or cached by this site.
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