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Project comparison
Evidently vs Ray
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Evidently
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
7.5K
Stars
0
Weekly
39/100
Health
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
Quick Take
Adoption
Ray has the larger GitHub footprint with 42.5K 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 | Evidently | Ray |
|---|---|---|
| GitHub stars | 7.5K | 42.5K |
| Weekly growth | 0 | +72 |
| Health score | 39 | 79 |
| Contributors | 97 | 1.6K |
| Commits per week | 1.2 | 87.6 |
| Open issues | 272 | 3.5K |
| Language | Jupyter Notebook | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last commit | 10d ago | 14h ago |
| Last release | v0.7.21 | ray-2.55.1 |
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