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Spreadsheets · head to head

Metabase vs MLflow

Metabase logo

Metabase

Spreadsheets

Fast analytics with the friendly UX

From
Free
Rated
-
Full reviewWebsite
MLflow logo

MLflow

Machine Learning

Open source platform for managing the ML lifecycle

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Metabase aI Service charges $3.75 per 1 million tokens (after 1M free tokens included); MLflow requires infrastructure setup: teams must manage MLflow tracking server, database, and artifact storage themselves
  • They diverge on capability: Metabase covers No-code Query Builder, MLflow covers Experiment tracking.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Metabase and MLflow actually diverge.

Attributes where Metabase and MLflow differ
AttributeMetabaseMLflow
Pricing modelfreemiumopen-source
PlatformsWeb, Self-hosted cloudWeb, Python API, REST API
CategorySpreadsheetsMachine Learning
Founded20142018

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Metabase

  • No-code Query Builder
  • SQL Editor
  • Interactive Dashboards
  • Alerts
  • Embedding
  • PostgreSQL
  • MySQL
  • MongoDB

Only in MLflow

  • Experiment tracking
  • Model registry
  • Model packaging
  • Deployment
  • Project organization
  • TensorFlow
  • PyTorch
  • scikit-learn

What people use each for

The jobs each tool is most often brought in to do.

Metabase

  • Business intelligence and data exploration for non-technical usersnot MLflow
  • Embedded analytics for SaaS applicationsnot MLflow
  • Self-service reporting and dashboard creationnot MLflow
  • Integration with 40+ data sources including cloud warehousesnot MLflow

MLflow

  • Machine learningnot Metabase
  • Data analysisnot Metabase
  • Model trainingnot Metabase
  • Predictive analyticsnot Metabase

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Metabase

  • AI Service charges $3.75 per 1 million tokens (after 1M free tokens included)
  • Transforms cost $0.01 per run after 1,000 included runs per month
  • Advanced Transforms cost $0.02 per run after included allocation
  • Storage overages start at $2 per 1M rows (1M rows free)
  • All yearly plans offer 10% discount versus monthly, incentivizing annual commitment

MLflow

  • Requires infrastructure setup: teams must manage MLflow tracking server, database, and artifact storage themselves
  • Basic UI and visualization: lacks rich interactive dashboards and real-time monitoring compared to commercial platforms
  • Limited collaboration: no built-in role-based access control or multi-user management features
  • Production monitoring gaps: drift detection, explainability, and alerting require separate dedicated tools

Pricing, plan by plan

Metabase

Free
  • Open SourceFree
    • Unlimited users
    • Unlimited questions and dashboards
    • AI-powered query generation
  • Starter$90/month
    • Email and chat support
    • $100/month standard monthly billing
    • 20+ data connectors
  • Pro$517.5/month
    • $575/month standard monthly
    • Row/column-level permissions
    • SSO
  • Enterprise$20000/year
    • Dedicated success engineer
    • 1-day support response SLA
    • Air-gapped deployment

MLflow

Free
  • Open SourceFree
    • Experiment tracking
    • Model registry
    • Deployment tools

Which should you pick?

Choose Metabase if

  • You need no-code query builder.
  • You want to start without paying.
  • You work on Web, Self-hosted cloud.
  • You also want sql editor.
Metabase review

Choose MLflow if

  • You need experiment tracking.
  • You want to start without paying.
  • You work on Web, Python API, REST API.
  • You also want model registry.
MLflow review

Questions people ask

Is Metabase or MLflow better?
Neither clearly leads. Metabase starts at Free and MLflow at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Metabase or MLflow?
Metabase starts at Free and MLflow at Free.
Does Metabase or MLflow run on more platforms?
Metabase runs on Web, Self-hosted cloud. MLflow runs on Web, Python API, REST API.
Can I use Metabase for free?
Both have a free tier, so you can try either at no cost before committing.
What is Metabase best used for?
Metabase is most often used for business intelligence and data exploration for non-technical users, embedded analytics for saas applications, self-service reporting and dashboard creation, integration with 40+ data sources including cloud warehouses. Of those, business intelligence and data exploration for non-technical users and embedded analytics for saas applications are not what MLflow is typically brought in for.
What can Metabase do that MLflow cannot?
Metabase covers No-code Query Builder, SQL Editor, Interactive Dashboards, Alerts. MLflow covers Experiment tracking, Model registry, Model packaging, Deployment.

Answered from the vendors’ own pages

Metabase: How much does Metabase cost?

Metabase Open Source is free for self-hosted deployments with unlimited users and dashboards. Cloud-hosted Starter tier costs $90/month annually ($100/month monthly) with Pro at $517.50/month annually ($575/month monthly). Enterprise plans start at $20,000 per year.

Source
MLflow: Is MLflow free to use?

Yes, MLflow is completely open-source and free. However, teams typically incur infrastructure costs for hosting and maintaining the MLflow tracking server. Databricks offers Managed MLflow as a commercial option for cloud deployment.

Source
Metabase: Does Metabase charge for additional users?

Yes, Metabase charges per-user fees beyond included users. Starter includes 5 users at $6 per additional user per month. Pro includes 10 users at $12 per additional user per month. Enterprise pricing is custom.

Source
MLflow: Can MLflow track experiments for different ML frameworks?

Yes, MLflow is framework-agnostic and works with TensorFlow, PyTorch, scikit-learn, XGBoost, and any other ML framework. This flexibility is a core design principle allowing teams to use diverse tools.

Source
Metabase: What usage-based fees does Metabase charge?

Metabase charges $3.75 per 1 million tokens for AI services (after 1M free tokens), $0.01 per transform run after 1,000 included per month, $0.02 for advanced transforms, and storage overages at $2 per 1M rows beyond the included 1M rows.

Source
MLflow: Does MLflow include a model registry?

Yes, MLflow Model Registry (added in 2018) provides a central model store with versioning, stage transitions, and deployment tracking. This enables production model governance and lineage tracking.

Source
MLflow: What are MLflow's main limitations?

MLflow requires significant infrastructure setup and maintenance. The UI is basic compared to commercial tools, collaboration is limited without third-party RBAC solutions, and production monitoring requires separate tools for drift detection and alerting.

Source
MLflow: Can MLflow handle LLM and agent tracing?

MLflow added LLM and agent tracing capabilities in recent versions, though the native support is limited compared to specialized LLM observability platforms that replaced weak LLM tracing.

Source
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