Apache Airflow

The Apache Software Foundation's platform for writing data pipelines as Python code, then scheduling and monitoring them across a pool of workers.

47.3k stars, 18.3k forks Python On GitHub since April 2015

Visit website View on GitHub How to run it

What is Apache Airflow?

In Airflow you define workflows, called Dags, in Python: tasks and the order they run in. The scheduler starts tasks on workers when their dependencies are met, and a web interface shows each run, its logs and its failures. Because pipelines are code, they live in Git and go through review and tests like any other software. Airflow is a top-level Apache project with a large set of provider packages for databases, clouds and data tools.

Good fit if

  • You run batch data pipelines, ETL or machine-learning jobs on a schedule.
  • Your team writes Python and wants pipelines versioned and reviewed like code.
  • You run Kubernetes: the repository includes an official Helm chart.

Look elsewhere if

  • You want workflows in YAML or a visual editor rather than Python: Kestra.
  • You need low-latency, event-driven application workflows: Temporal or Hatchet are designed for that.

Before you adopt it

Airflow is Apache-2.0, governed by the Apache Software Foundation, and every feature in the repository is free; several companies sell managed Airflow. It is a substantial system to operate, with a scheduler, workers, a metadata database and a web server, so plan for real operations work or a managed service.

Drafted with AI from the project's README and repository data, then checked against that data on 30 October 2026. Report a correction

Apache Airflow health: is it still maintained?

87 of 100, actively developed

  • Activity
    2,529 commits in the last 90 days, the latest on 1 November 2026.
    30 / 30
  • Contributors
    44 people wrote the latest 100 commits; the most active wrote 23% of them.
    20 / 20
  • Releases
    14 releases in the last 12 months; the latest, 3.3.2, on 17 September 2026.
    19 / 20
  • Replies to issues
    Too few recent issues from outside the team to measure, so this part gets a neutral score.
    10 / 20
  • Security practices
    OpenSSF Scorecard 7.7 of 10.
    8 / 10

Read from GitHub on 1 November 2026. How the score works

Apache Airflow license: is it open source?

Apache Airflow uses Apache-2.0, an open-source license approved by the OSI.

  1. April 2015First published on GitHub.
  2. TodayApache-2.0.

How to run Apache Airflow yourself

Docker
Dockerfile or compose file in the repository
Compose file
None in the repository
Setup effort
Not rated: no compose file to judge from
Kubernetes
Helm chart in the repository
Desktop and mobile
No app builds in GitHub releases
Interface languages
19 languages

Install instructions: airflow.apache.org or the README on GitHub.

Alternatives to Apache Airflow

  • DagsterAn orchestration platform for the development, production, and observation of data assets. 68 health · Apache-2.0 · 16.4k stars
  • KestraOrchestrate everything, everywhere. The open-source control plane for workflows across data, infrastructure,… 85 health · Apache-2.0 · 30.1k stars
  • Argo WorkflowsWorkflow Engine for Kubernetes 86 health · Apache-2.0 · 17.1k stars
  • PrefectPrefect is a workflow orchestration framework for building resilient data pipelines in Python. 80 health · Apache-2.0 · 24.1k stars
  • Apache DolphinSchedulerApache DolphinScheduler is the modern data orchestration platform. Agile to create high performance workflow… 83 health · Apache-2.0 · 14.6k stars

All 33 projects in Workflow automation

Questions about Apache Airflow

Is Apache Airflow open source?

Yes. Apache Airflow is published under Apache-2.0, an OSI-approved open-source license.

Is Apache Airflow still maintained?

Its health score is 87 of 100 (actively developed). It had 2,529 commits in the last 90 days, the latest on 1 November 2026, and its latest release came out on 17 September 2026.

How do I run Apache Airflow?

You can run it with Docker, on Kubernetes with the Helm chart in the repository. The README on GitHub has the exact steps.

What are the alternatives to Apache Airflow?

Close alternatives in the Workflow automation category include Dagster, Kestra, Argo Workflows.