head to head · open source
airflow vs riko
airflow has 47,344 GitHub stars, 18,287 forks, 1,831 open issues and last shipped yesterday. riko has 1,605 stars, 75 forks, 25 open issues and last shipped yesterday. airflow leads on adoption by 2,850% (47,344 vs 1,605 stars). airflow is written in Python under Apache-2.0; riko is written in Python under MIT. airflow has attracted 39% as many forks as stars, riko 5%. riko 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.
← all 20902 open source comparisons
Side by side
| airflow | riko | |
|---|---|---|
| GitHub stars | ★ 47K | ★ 1.6K |
| License | Apache-2.0 | MIT |
| Written in | Python | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 18K | ⑂ 75 |
| 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 riko if
- You want the riko feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and riko 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 riko
riko: composable stream processing for Python ============================================= .. contents:: :local: :depth: 2 Introduction riko is a pure Python library for building data processing streams . riko combines reusable, configuration driven modular pipes with synchronous , asynchronous , and parallel execution APIs. It is particularly useful for processing RSS feeds, web content, text, and structured files. riko also supplies a command line interface for executing flows , i.e., stream processors aka pipelines . Requirements & Installation riko has been tested and is known to work on Python 3.12, 3.13…
More in Data & Analytics
Related comparisons
More Data Engineering & Integration projects
Compare either of these against the rest of the Data Engineering & Integration field.
Frequently asked questions
Is airflow or riko more popular?
airflow has 47,344 GitHub stars and riko has 1,605. airflow has the larger community by that measure.
Are airflow and riko free?
Both are open source. airflow is licensed under Apache-2.0 and riko under MIT. Neither carries a licence fee.
What is the difference between airflow and riko?
airflow is written in Python and riko 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 riko?
Choose airflow if you want the larger community (47,344 stars) or its Apache-2.0 licence terms. Choose riko if its feature set, stack or MIT licence fits better. Both are self-hostable.