head to head · open source
airflow vs sycamore
airflow has 47,350 GitHub stars, 18,299 forks, 1,831 open issues and last shipped yesterday. sycamore has 605 stars, 71 forks, 57 open issues and last shipped 3 months ago. airflow leads on adoption by 7,726% (47,350 vs 605 stars). airflow is written in Python under Apache-2.0; sycamore is written in Python under Apache-2.0. airflow has attracted 39% as many forks as stars, sycamore 12%. airflow was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (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 | sycamore | |
|---|---|---|
| GitHub stars | ★ 47K | ★ 605 |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-08-01 |
| Forks | ⑂ 18K | ⑂ 71 |
| 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 sycamore if
- You want the sycamore 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 sycamore 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 sycamore
Sycamore is an open source, AI powered document processing engine for ETL, RAG, LLM based applications, and analytics on unstructured data. Sycamore can partition and enrich a wide range of document types including reports, presentations, transcripts, manuals, and more. It can analyze and chunk complex documents such as PDFs and images with embedded tables, figures, graphs, and other infographics. Check out an example notebook. For processing documents, Sycamore leverages Aryn DocParse (formerly known as the Aryn Partitioning Service), a serverless, GPU powered API for segmenting and labeling documents, doing…
read the full sycamore overview →
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Frequently asked questions
Is airflow or sycamore more popular?
airflow has 47,350 GitHub stars and sycamore has 605. airflow has the larger community by that measure.
Are airflow and sycamore free?
Both are open source. airflow is licensed under Apache-2.0 and sycamore under Apache-2.0. Neither carries a licence fee.
What is the difference between airflow and sycamore?
airflow is written in Python and sycamore 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 sycamore?
Choose airflow if you want the larger community (47,350 stars) or its Apache-2.0 licence terms. Choose sycamore if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.