MLflow
Top pickThe open standard. Tracking, registry, projects and deployment in one.
93
sovereigntyMLflow is the most widely adopted open ML platform, and its scope is why: experiment tracking, a model registry with stage transitions, reproducible project packaging and deployment tooling, all Apache-2.0. It runs as a local file store for one person or as a server with a database and object store for a team, integrates with essentially every framework, and is supported natively by every major cloud — so it is the option least likely to become a dead end.
OPEN SOURCEApache-2.0SELF-HOSTLOCAL-FIRST
LicenseApache-2.0
PricingFree, Apache-2.0. Managed versions are sold by the clouds if you want one.
Open sourceYes
Self-hostableYes
Local-first dataYes
What it does well
- +Covers tracking, registry, packaging and deployment — not just tracking
- +The de facto standard; integrated with every major framework and cloud
- +Scales from a local directory to a full server deployment
- +Apache-2.0 with unlimited seats
Where it falls short
- −UI is functional rather than pleasant, and slows on very large run counts
- −Team deployment means running a server, a database and object storage
- −No built-in sweep orchestration comparable to W&B's
MLflow as an alternative to
Where MLflow shows up in our comparisons, and how it ranked.
MLflow head-to-head
Straight comparisons against the tools people weigh it against.