Decision Workspace
irithyll vs rill-ml vs sklears-ensemble
Side-by-side comparison of Rust crates
54
irithyll
experimentalv10.0.1
Streaming ML in Rust -- gradient boosted trees, neural architectures (TTT/KAN/MoE/Mamba/SNN), AutoML, kernel methods, and composable pipelines
49
rill-ml
experimentalv0.5.1
Lightweight, serializable online machine learning for Rust applications and streaming data.
59
sklears-ensemble
experimentalv0.1.2
Ensemble methods for sklears: Random Forest, Gradient Boosting, AdaBoost
Core Metrics
| irithyll | rill-ml | sklears-ensemble | |
|---|---|---|---|
| Health Score | 54 | 49 | 59 |
| Total Downloads | 1.4K | 12 | 629 |
| 30d Downloads | 0 | 0 | 0 |
| Dependents | 0 | 1 | 17 |
| Releases | 62 | 1 | 7 |
| Last Updated | 63d ago | today | 14d ago |
| Age | 4m | 1d | 9m |
Health Breakdown
irithyll
Maintenance
15
Quality
14
Community
6
Popularity
4
Documentation
15
rill-ml
Maintenance
13
Quality
13
Community
7
Popularity
1
Documentation
15
sklears-ensemble
Maintenance
21
Quality
14
Community
9
Popularity
3
Documentation
12
Technical Details
| irithyll | rill-ml | sklears-ensemble | |
|---|---|---|---|
| Version | 10.0.1 | 0.5.1 | 0.1.2 |
| Stable (≥1.0) | ✓ Yes | ✗ No | ✗ No |
| License | MIT OR Apache-2.0 | MIT | Apache-2.0 |
| Dependencies | 18 | 8 | 10 |
| Crate Size | 5.1MB | 182KB | 204KB |
| Features | 13 | 2 | 6 |
| Yanked % | 0.0% | 0.0% | 0.0% |
| Edition | 2021 | 2024 | 2021 |
| MSRV | 1.75 | 1.85 | 1.89 |
| Owners | 1 | 1 | 1 |
Links
Quick Verdict
- •sklears-ensemble leads with a health score of 59/100, but none of the options score above 80.
- •irithyll has the most downloads (1.4K), suggesting wider adoption.
- •rill-ml, sklears-ensemble are pre-1.0 — API may change.