head to head · open source
airflow vs CloudQuery
airflow has 47,301 GitHub stars, 18,202 forks, 1,831 open issues and last shipped yesterday. CloudQuery has 6,545 stars, 567 forks, 166 open issues and last shipped yesterday. airflow leads on adoption by 623% (47,301 vs 6,545 stars). airflow is written in Python under Apache-2.0; CloudQuery is written in Go under MPL-2.0. airflow has attracted 38% as many forks as stars, CloudQuery 9%. airflow was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (data-engineering, data-integration, elt), 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 | CloudQuery | |
|---|---|---|
| GitHub stars | ★ 47K | ★ 6.5K |
| License | Apache-2.0 | MPL-2.0 |
| Written in | Python | Go |
| Last push | 2026-10-28 | 2026-10-28 |
| Forks | ⑂ 18K | ⑂ 567 |
| 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 CloudQuery if
- You want the CloudQuery feature set and don't need the biggest community
- You prefer the MPL-2.0 license terms
- Your stack matches Go
- You evaluated both and CloudQuery 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 CloudQuery
CloudOps, without the chaos CloudQuery is a cloud asset inventory built for platform teams. Sync your cloud infrastructure metadata into your data warehouse, powering insights and automation. Unify data and provide context across AWS, Azure, GCP, and 70+ cloud and SaaS sources such as Wiz, Finout, and GitHub. Installation Check out the quickstart guide for install guides for Linux and Windows and for step by step instructions on completing your first sync with CloudQuery. Why CloudQuery? Specialized plugin coverage Support for cloud infrastructure, security, and FinOps sources with normalization, rate limit…
read the full CloudQuery overview →
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Frequently asked questions
Is airflow or CloudQuery more popular?
airflow has 47,301 GitHub stars and CloudQuery has 6,545. airflow has the larger community by that measure.
Are airflow and CloudQuery free?
Both are open source. airflow is licensed under Apache-2.0 and CloudQuery under MPL-2.0. Neither carries a licence fee.
What is the difference between airflow and CloudQuery?
airflow is written in Python and CloudQuery 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 CloudQuery?
Choose airflow if you want the larger community (47,301 stars) or its Apache-2.0 licence terms. Choose CloudQuery if its feature set, stack or MPL-2.0 licence fits better. Both are self-hostable.