← Back to Leaderboard
Project comparison
Made With ML vs Airflow
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Made With ML
Learn how to develop, deploy and iterate on production-grade ML applications.
47.6K
Stars
0
Weekly
36/100
Health
Airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
45.4K
Stars
0
Weekly
71/100
Health
Quick Take
Adoption
Made With ML has the larger GitHub footprint with 47.6K stars.
Momentum
Made With ML is currently growing faster at 0 stars this week.
Maintenance
Airflow has the stronger health score at 71/100.
Side-by-side Metrics
| Signal | Made With ML | Airflow |
|---|---|---|
| GitHub stars | 47.6K | 45.4K |
| Weekly growth | 0 | 0 |
| Health score | 36 | 71 |
| Contributors | 1 | 4.4K |
| Commits per week | 0.1 | 181.2 |
| Open issues | 25 | 1.7K |
| Language | Jupyter Notebook | Python |
| License | MIT | Apache-2.0 |
| Last commit | 2mo ago | 16h ago |
| Last release | v1.1.0 | helm-chart/1.21.0 |
Weekly AI open-source movers
Get the fastest-growing projects, useful MCP servers, and technical reads in one weekly email.