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mlflow.org

CodingVerifiedVerified#658 Ranked

Open-source platform for managing the machine learning lifecycle.

Quick Information

Category:
Coding
Pricing:
Freemium
Platforms:
Web, Windows, macOS, Linux
Free Plan:
Yes
API Available:
Yes
Last Verified:
September 2026

What Is MLflow?

MLflow is an open-source platform for managing the machine learning lifecycle, remaining Apache 2.0 licensed with an unchanged cost structure (fully free, self-hosted) as of April 2026. The main cost drivers for a self-hosted MLflow deployment are storage for artifacts and runs, and compute for the tracking server and model serving — the software itself carries no license fee.

For teams wanting a managed option rather than self-hosting, MLflow is available as part of Databricks' interactive workloads, billed under Databricks' standard DBU (Databricks Unit) consumption model across Premium and Enterprise tiers (a free MLflow on Databricks Free Edition is available for those just getting started). A significant related platform change: Databricks retired its Standard tier — new Standard workspace creation was blocked after April 1, 2026, with remaining Standard workspaces automatically upgraded to Premium by October 2026.

It's aimed at ML teams wanting a genuinely free, open-source lifecycle management platform they can self-host, or a managed alternative through Databricks for teams wanting infrastructure handled for them, with the Databricks Standard tier retirement being an important recent platform change for existing Databricks-based MLflow users to be aware of. See our Developer Tools directory for related ML tools like LangSmith.

What Can You Use MLflow For?

ML experiment tracking

Tracks machine learning experiments, runs, and metrics.

Model lifecycle management

Manages the full lifecycle of ML models from development to deployment.

Managed MLflow via Databricks

Runs MLflow as a managed service within the Databricks platform.

MLflow Features

  • Experiment tracking — Tracks ML experiments, parameters, and metrics.
  • Model registry — Manages model versions and lifecycle stages.
  • Databricks integration — Runs as a managed service within Databricks, billed via the DBU consumption model.

Who Is MLflow For?

  • ML teams — Tracks experiments and manages model lifecycle using a free, open-source platform.
  • Databricks users — Runs managed MLflow within Databricks, billed under the standard DBU model.

MLflow Pros & Limitations

What We Like

  • Genuinely free, open-source, Apache 2.0-licensed core with unchanged cost structure
  • Self-hosting means no license fee — costs are limited to your own storage and compute
  • Free MLflow on Databricks Free Edition provides an accessible managed starting point

Limitations

  • Self-hosting requires managing your own storage and compute infrastructure costs
  • Databricks Standard tier retirement (blocked new creation after April 1, 2026) affects existing Standard-tier users
  • Managed Databricks pricing follows the DBU consumption model, which requires understanding usage-based billing

MLflow Pricing

PlanPriceMain Features
Open source (self-hosted)FreeFull ML lifecycle management, pay only for your own infrastructure
Databricks Free EditionFreeManaged MLflow starting point
Databricks Premium/EnterpriseDBU consumption-basedManaged MLflow within Databricks workspace

Pricing was last verified September 2026. Check the official website for the latest pricing.

Check Current Pricing

AI Listing Jungle Ranking

Global Rank:
#658
Overall Score:
21.6/100
Monthly Users:
–
Rank Change:
▼ 18

This ranking reflects AI Listing Jungle's own independent scoring methodology and is not an endorsement by MLflow or its company. How Our Rankings Work

Frequently Asked Questions

Is MLflow free?

Yes, the open-source core is Apache 2.0-licensed and free to self-host.

What are the main costs of self-hosting MLflow?

Storage for artifacts and runs, plus compute for the tracking server and model serving.

What happened to Databricks Standard tier?

New Standard workspace creation was blocked after April 1, 2026, with remaining workspaces upgraded to Premium by October 2026.

Is there a free managed option?

Yes, MLflow on Databricks Free Edition is available for those getting started.

Our Take

MLflow's genuinely free, unchanged Apache 2.0 licensing makes self-hosting a real no-license-fee option, with costs limited to your own infrastructure.

Databricks-based MLflow users should note the Standard tier retirement, since remaining Standard workspaces will be automatically upgraded to Premium by October 2026.

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