head to head · open source
airflow vs automate-dv
airflow has 47,350 GitHub stars, 18,299 forks, 1,831 open issues and last shipped yesterday. automate-dv has 598 stars, 157 forks, 53 open issues and last shipped 9 months ago. airflow leads on adoption by 7,818% (47,350 vs 598 stars). airflow is written in Python under Apache-2.0; automate-dv is written in various languages under Apache-2.0. airflow has attracted 39% as many forks as stars, automate-dv 26%. airflow was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (elt, etl), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| airflow | automate-dv | |
|---|---|---|
| GitHub stars | ★ 47K | ★ 598 |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | — |
| Last push | 2026-11-02 | 2026-02-05 |
| Forks | ⑂ 18K | ⑂ 157 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick airflow if
- You weight community size — 47K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick automate-dv if
- You want the automate-dv feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- You evaluated both and automate-dv fits your workflow better
About airflow
Apache Airflow Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows. When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative. Use Airflow to author workflows (Dags) that orchestrate tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on Dags a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when…
read the full airflow overview →
About automate-dv
Changelog and past doc versions AutomateDV by Datavault Build your own Data Vault data warehouse! AutomateDV is a free to use dbt package that generates & executes the ETL you need to run a Data Vault 2.0 Data Warehouse on your data platform. What does AutomateDV offer? productivity gains, fewer errors multi threaded execution of the generated SQL your data modeller can generate most of the ETL code directly from their mapping metadata your ETL developers can focus on the 5% of the SQL code that is different dbt generates documentation and data flow diagrams powered by dbt, a registered trademark of dbt Labs…
read the full automate-dv overview →
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Frequently asked questions
Is airflow or automate-dv more popular?
airflow has 47,350 GitHub stars and automate-dv has 598. airflow has the larger community by that measure.
Are airflow and automate-dv free?
Both are open source. airflow is licensed under Apache-2.0 and automate-dv under Apache-2.0. Neither carries a licence fee.
What is the difference between airflow and automate-dv?
airflow is written in Python and automate-dv in various languages. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, airflow or automate-dv?
Choose airflow if you want the larger community (47,350 stars) or its Apache-2.0 licence terms. Choose automate-dv if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.