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Project comparison
Evidently vs Airflow
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
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
Evidently is currently growing faster at 0 stars this week.
Maintenance
Airflow has the stronger health score at 71/100.
Side-by-side Metrics
| Signal | Evidently | Airflow |
|---|---|---|
| GitHub stars | 7.5K | 45.4K |
| Weekly growth | 0 | 0 |
| Health score | 39 | 71 |
| Contributors | 97 | 4.4K |
| Commits per week | 1.2 | 181.2 |
| Open issues | 272 | 1.7K |
| Language | Jupyter Notebook | Python |
| License | Apache-2.0 | Apache-2.0 |
| Last commit | 10d ago | 15h ago |
| Last release | v0.7.21 | helm-chart/1.21.0 |
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