Apache Airflow vs Dagster
A side-by-side comparison of two self-hosted automation & workflows options — licensing, setup difficulty, resource needs, and what each one replaces.
Not the right match-up?
Apache Airflow
Programmatically author, schedule and monitor workflows
VS
Dagster
Data orchestrator for the full development lifecycle
| Feature | Apache Airflow | Dagster |
|---|---|---|
| Category | Automation & Workflows | Automation & Workflows |
| License | Apache-2.0 | Apache-2.0 |
| Language | Python | Python |
| Setup difficulty | Hard | Medium |
| Min. RAM | 4,096 MB | 2,048 MB |
| Deployment | docker, kubernetes, helm | docker, kubernetes, helm |
| GitHub stars | ★ 46,409 | ★ 15,943 |
| First released | 2015 | 2019 |
| Replaces | AWS Step Functions, Azure Data Factory | AWS Step Functions, Azure Data Factory |
Why pick each one
Frequently asked questions
Is Apache Airflow or Dagster better?
Neither is universally better. Apache Airflow has the larger community, while Dagster is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.
Are Apache Airflow and Dagster free and open-source?
Yes. Apache Airflow is licensed under Apache-2.0 and Dagster under Apache-2.0. Both can be self-hosted at no software cost.
Can I run Apache Airflow and Dagster with Docker?
Apache Airflow: yes. Dagster: yes.