ModelDB
ModelDB is an open-source system for versioning machine learning models and tracking metadata across development, deployment, and live monitoring.
What ModelDB is
ModelDB is an open-source system for versioning machine learning models and tracking metadata across development, deployment, and live monitoring. It records code, data, configuration, and environment details to help preserve the context needed for reproducibility. Experiment tools include management, performance dashboards, and report sharing. Flexible metadata logging can capture metrics, artifacts, tags, and user information. ModelDB provides Python and Scala clients and lists TensorFlow and PyTorch integrations. It supports pluggable storage and is configured and verified with PostgreSQL. The project says it works on Docker and Kubernetes and documents Docker Compose and Helm deployment options. It is available through an API, web interface, or self-hosted deployment. The open-source edition is free under the Apache 2.0 license. For support, the project directs users to GitHub issues for bug reports and feature requests, and Slack for questions and help. The README says interested users can contact [email protected] about a hosted version.
Good
- Free under Apache 2.0
- Tracks models through development and monitoring
- Python and Scala clients
- Docker Compose and Helm deployment options
Watch out
- Self-hosted deployment is the listed free plan
- Hosted version requires contacting the project
Who it suits
It suits teams that need to manage, version, and audit machine learning models over their lifecycle. It is particularly relevant to users comfortable with self-hosting and the documented deployment options.
Verdict
ModelDB combines model versioning, experiment management, and lifecycle metadata tracking in a free open-source package. Teams should review its self-hosted deployment approach and support channels before choosing it.
Plans and prices
From ModelDB's own pricing page, checked 9 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Open-source ModelDB | Free | Apache 2.0 licensed · self-hosted deployment |
The facts
Each one read from ModelDB's own pages, with the date it was checked.
What it does
- Clients and integrations
- ModelDB provides Python and Scala clients and lists TensorFlow and PyTorch integrations.checked 9 Oct 2026
- Deployment
- The project says it works on Docker and Kubernetes and documents Docker Compose and Helm deployment options.checked 9 Oct 2026
- Experiment management
- It supports experiment management, performance dashboards, and report sharing.checked 9 Oct 2026
- Hosted option
- The README says to contact [email protected] about a hosted version.checked 9 Oct 2026
- Intended users
- The project is for managing, versioning, and auditing machine learning models across their lifecycle.checked 9 Oct 2026
- License
- ModelDB is licensed under Apache 2.0.checked 9 Oct 2026
- Lifecycle tracking
- It tracks models during development, deployment, and live monitoring.checked 9 Oct 2026
- Metadata
- Its flexible metadata logging includes metrics, artifacts, tags, and user information.checked 9 Oct 2026
- Purpose
- ModelDB versions machine learning models and tracks ML metadata across the model lifecycle.checked 9 Oct 2026
- Reproducibility
- It records model ingredients including code, data, configuration, and environment to support reproducibility.checked 9 Oct 2026
- Storage
- It supports pluggable storage systems and is configured and verified out of the box with PostgreSQL.checked 9 Oct 2026
- Support
- The project directs users to GitHub issues for bug reports and feature requests and to Slack for questions and help.checked 9 Oct 2026
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