head to head · open source
airflow vs go-streams
airflow has 47,350 GitHub stars, 18,299 forks, 1,831 open issues and last shipped yesterday. go-streams has 2,177 stars, 173 forks, 11 open issues and last shipped 10 months ago. airflow leads on adoption by 2,075% (47,350 vs 2,177 stars). airflow is written in Python under Apache-2.0; go-streams is written in Go under MIT. airflow has attracted 39% as many forks as stars, go-streams 8%. 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 | go-streams | |
|---|---|---|
| GitHub stars | ★ 47K | ★ 2.2K |
| License | Apache-2.0 | MIT |
| Written in | Python | Go |
| Last push | 2026-11-02 | 2026-01-14 |
| Forks | ⑂ 18K | ⑂ 173 |
| 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 go-streams if
- You want the go-streams feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Go
- You evaluated both and go-streams 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 go-streams
go streams go streams provides a lightweight and efficient stream processing framework for Go. Its concise DSL allows for easy definition of declarative data pipelines using composable sources, flows, and sinks. Wiki) In computing, a pipeline, also known as a data pipeline, is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time sliced fashion. Some amount of buffer storage is often inserted between elements. Overview The core module has no external dependencies and provides three…
read the full go-streams overview →
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Frequently asked questions
Is airflow or go-streams more popular?
airflow has 47,350 GitHub stars and go-streams has 2,177. airflow has the larger community by that measure.
Are airflow and go-streams free?
Both are open source. airflow is licensed under Apache-2.0 and go-streams under MIT. Neither carries a licence fee.
What is the difference between airflow and go-streams?
airflow is written in Python and go-streams in Go. 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 go-streams?
Choose airflow if you want the larger community (47,350 stars) or its Apache-2.0 licence terms. Choose go-streams if its feature set, stack or MIT licence fits better. Both are self-hostable.