head to head · open source
airflow vs sql-data-warehouse-project
airflow has 47,416 GitHub stars, 18,323 forks, 1,831 open issues and last shipped yesterday. sql-data-warehouse-project has 1,064 stars, 748 forks, 5 open issues and last shipped 2 days ago. airflow leads on adoption by 4,356% (47,416 vs 1,064 stars). airflow is written in Python under Apache-2.0; sql-data-warehouse-project is written in TSQL under MIT. airflow has attracted 39% as many forks as stars, sql-data-warehouse-project 70%. airflow was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (data-engineering, 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 | sql-data-warehouse-project | |
|---|---|---|
| GitHub stars | ★ 47K | ★ 1.1K |
| License | Apache-2.0 | MIT |
| Written in | Python | TSQL |
| Last push | 2026-11-07 | 2026-11-06 |
| Forks | ⑂ 18K | ⑂ 748 |
| 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 sql-data-warehouse-project if
- You want the sql-data-warehouse-project feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches TSQL
- You evaluated both and sql-data-warehouse-project 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 sql-data-warehouse-project
Data Warehouse and Analytics Project The materials of the data warehouse project: the source files, every script from the videos, and the docs. ⭐ If this project helps you, star the repository so other learners can find it too. You take raw files from two systems, a CRM and an ERP, and build one data warehouse in SQL Server. At the end, the data is clean and ready for analysis. New here? Open the setup guide in the 00 setup folder. It walks you through installing SQL Server and creating the database, on Windows and Mac, with the fixes for the common errors. The project reads the six files from C:\sql\dwh…
read the full sql-data-warehouse-project overview →
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Frequently asked questions
Is airflow or sql-data-warehouse-project more popular?
airflow has 47,416 GitHub stars and sql-data-warehouse-project has 1,064. airflow has the larger community by that measure.
Are airflow and sql-data-warehouse-project free?
Both are open source. airflow is licensed under Apache-2.0 and sql-data-warehouse-project under MIT. Neither carries a licence fee.
What is the difference between airflow and sql-data-warehouse-project?
airflow is written in Python and sql-data-warehouse-project in TSQL. 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 sql-data-warehouse-project?
Choose airflow if you want the larger community (47,416 stars) or its Apache-2.0 licence terms. Choose sql-data-warehouse-project if its feature set, stack or MIT licence fits better. Both are self-hostable.