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Project comparison
Ray vs Airflow
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
42.5K
Stars
+72
Weekly
79/100
Health
Airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
45.4K
Stars
0
Weekly
71/100
Health
Quick Take
Adoption
Airflow has the larger GitHub footprint with 45.4K stars.
Momentum
Ray is currently growing faster at +72 stars this week.
Maintenance
Ray has the stronger health score at 79/100.
Side-by-side Metrics
| Signal | Ray | Airflow |
|---|---|---|
| GitHub stars | 42.5K | 45.4K |
| Weekly growth | +72 | 0 |
| Health score | 79 | 71 |
| Contributors | 1.6K | 4.4K |
| Commits per week | 87.6 | 181.2 |
| Open issues | 3.5K | 1.7K |
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last commit | 15h ago | 15h ago |
| Last release | ray-2.55.1 | helm-chart/1.21.0 |
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