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MLflow vs ClearML
This comparison was retrieved by database IDs selected from the catalog.
MLflow
MLflow (Databricks)
ClearML
ClearML
Open source Apache 2.0 licence. Free to self-host. Managed MLflow included in Databricks. Community and enterprise support available.
Open source self-hosted is free. ClearML Cloud managed from $13/month. Enterprise custom.
Open source Apache 2.0 licence. Self-hosted deployment keeps data on customer infrastructure. Managed Databricks MLflow subject to Databricks data handling. Enterprise support available.
Open source self-hosted keeps all data on customer infrastructure. ClearML Cloud subject to ClearML's data handling policy. Enterprise includes data handling agreements.
Self-hosted MLflow keeps all experiment data on customer infrastructure. Databricks Managed MLflow processes data on Databricks' cloud infrastructure. Review Databricks privacy policy for managed deployments.
Self-hosted deployment keeps all ML experiment data on customer infrastructure. ClearML Cloud transmits experiment data to ClearML's servers — review privacy policy.
- De facto standard with enormous community, tutorial, and integration ecosystem
- Apache 2.0 licence — completely free for any use including commercial
- Autolog integration with all major frameworks requires minimal instrumentation code
- Databricks managed MLflow provides enterprise infrastructure without self-hosting overhead
- Completely free self-hosted deployment for teams with privacy requirements or budget constraints
- Open source transparency — inspect and modify the platform code for custom needs
- Auto-magic experiment tracking integrates without code changes for common ML frameworks
- Comprehensive platform covering experiment to deployment rather than requiring multiple tools
- UI and visualisation less polished than commercial alternatives like Weights & Biases
- MLflow server self-hosting requires database and storage configuration for production use
- Model registry governance less mature than enterprise MLOps platforms for complex model management
- Self-hosted requires DevOps setup and maintenance overhead
- Community support for open source tier — enterprise support requires paid plan
- Less polished UI/UX than commercial alternatives like Weights & Biases
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