head to head · open source
airflow vs sqlmesh
airflow has 47,350 GitHub stars, 18,299 forks, 1,831 open issues and last shipped yesterday. sqlmesh has 3,344 stars, 484 forks, 304 open issues and last shipped yesterday. airflow leads on adoption by 1,316% (47,350 vs 3,344 stars). airflow is written in Python under Apache-2.0; sqlmesh is written in Python under Apache-2.0. airflow has attracted 39% as many forks as stars, sqlmesh 14%. 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 | sqlmesh | |
|---|---|---|
| GitHub stars | ★ 47K | ★ 3.3K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 18K | ⑂ 484 |
| 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 sqlmesh if
- You want the sqlmesh feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and sqlmesh 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 sqlmesh
SQLMesh is a project of the Linux Foundation . SQLMesh is a next generation data transformation framework designed to ship data quickly, efficiently, and without error. Data teams can run and deploy data transformations written in SQL or Python with visibility and control at any size. It is more than just a dbt alternative. Core Features Get instant SQL impact and context of your changes, both in the CLI and in the SQLMesh VSCode Extension Virtual Data Environments See a full diagram of how Virtual Data Environments work Watch this video to learn more Create isolated development environments without data…
read the full sqlmesh overview →
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Frequently asked questions
Is airflow or sqlmesh more popular?
airflow has 47,350 GitHub stars and sqlmesh has 3,344. airflow has the larger community by that measure.
Are airflow and sqlmesh free?
Both are open source. airflow is licensed under Apache-2.0 and sqlmesh under Apache-2.0. Neither carries a licence fee.
What is the difference between airflow and sqlmesh?
airflow is written in Python and sqlmesh in Python. 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 sqlmesh?
Choose airflow if you want the larger community (47,350 stars) or its Apache-2.0 licence terms. Choose sqlmesh if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.