Alternatives
Self-hosted alternatives to MLflow
Projects in the registry that can run on your own hardware and serve at least one of the same use cases as MLflow.
- Source
- Registry relations over fetched repository records — the evidence sits on each repository page
- Verified
- Evidence not verified
- Confidence
- High
01How this list was built
- Compared against
- MLflow
- Delivery
- Cloud platforms
- Shared use cases
- Prediction from operational data, Choosing a model
- Selection rule
- open source, or self-hostable, and shares a use case
- Candidates found
- 2
02Alternatives
2
scikit-learn
Libraries
The standard Python library for classical machine learning: regression, classification, clustering, preprocessing pipelines and model evaluation on tabular data.
- Repository
- scikit-learn/scikit-learn
- Stars
- 67,301
- Licence
- BSD-3-Clause
- In stacks
- 1
Shares: Predictive analytics
XGBoost
Libraries
Gradient-boosted decision trees with distributed training and GPU support. The usual first model to try on a tabular prediction problem before anything more elaborate.
- Repository
- dmlc/xgboost
- Stars
- 28,777
- Licence
- Apache-2.0
- In stacks
- 1
Shares: Predictive analytics
03Repository facts
| Repository | Stars | Health |
|---|---|---|
| scikit-learn/scikit-learnscikit-learn: machine learning in Python | 67k | Maintenance 80%, Releases 60%, Contributors 50%, Issues 68%, Community 97%74 |
| dmlc/xgboostScalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow | 29k | Maintenance 80%, Releases 60%, Contributors 50%, Issues 85%, Community 89%74 |
04Ask about your own case
Which alternative is right depends on how many people will use it, what the data is and what you can operate. Ask and the answer is researched for your organisation.