Apache Airflow vs Maestral
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
Maestral
Lightweight Dropbox client that runs as a daemon
| Feature | Apache Airflow | Maestral |
|---|---|---|
| Category | Automation & Workflows | Automation & Workflows |
| License | Apache-2.0 | MIT |
| Language | Python | Python |
| Setup difficulty | Hard | Easy |
| Min. RAM | 4,096 MB | 256 MB |
| Deployment | docker, kubernetes, helm | binary, source |
| GitHub stars | ★ 46,409 | ★ 3,335 |
| First released | 2015 | 2019 |
| Replaces | AWS Step Functions, Azure Data Factory | Dropbox client |
Why pick each one
Choose Maestral if…
- Released under the MIT license
- Easy to set up — beginner-friendly
- Active community (3.3k GitHub stars)
- Written in Python
Frequently asked questions
Is Apache Airflow or Maestral better?
Neither is universally better. Apache Airflow has the larger community, while Maestral is simpler to set up (easy difficulty). Choose based on the comparison table above and your own setup.
Are Apache Airflow and Maestral free and open-source?
Yes. Apache Airflow is licensed under Apache-2.0 and Maestral under MIT. Both can be self-hosted at no software cost.
Can I run Apache Airflow and Maestral with Docker?
Apache Airflow: yes. Maestral: check the project docs for container support.