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Machine Learning · head to head

ClearML vs Lightdash

ClearML logo

ClearML

Machine Learning

Open-source MLOps platform for experiment tracking and orchestration

From
Free
Rated
-
Full reviewWebsite
Lightdash logo

Lightdash

Business Intelligence

Open-source BI for dbt users

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: ClearML broad scope means more to learn and more to run than a focused tracking tool; Lightdash requires existing dbt infrastructure, not suitable for teams without data models
  • They diverge on capability: ClearML covers Experiment tracking, Lightdash covers dbt Integration.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which ClearML and Lightdash actually diverge.

Attributes where ClearML and Lightdash differ
AttributeClearMLLightdash
Pricing modelOpen-source self-hosted, with paid hosted and enterprise tiersUnknown
PlatformsLinux, macOS, Windows, Docker, KubernetesWeb, Cloud (managed), Self-hosted (on-premise)
CategoryMachine LearningBusiness Intelligence
FoundedUnknown2021

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 ClearML

  • Experiment tracking
  • Remote execution
  • Data versioning
  • Pipelines

Only in Lightdash

  • dbt Integration
  • Metrics Layer
  • Dashboards
  • Scheduling
  • Version Control
  • dbt
  • BigQuery
  • Snowflake

What people use each for

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

ClearML

  • Tracking experiments across a team so results are reproduciblenot Lightdash
  • Moving training from laptops to shared GPU hardware without repackagingnot Lightdash
  • Versioning datasets alongside the experiments that consumed themnot Lightdash

Lightdash

  • Self-service analyticsnot ClearML
  • Data explorationnot ClearML
  • Ad-hoc reportingnot ClearML
  • Collaborative analysisnot ClearML
  • Embedded analyticsnot ClearML

Where each one falls short

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

ClearML

  • Broad scope means more to learn and more to run than a focused tracking tool
  • Self-hosting the server is real infrastructure — database, file storage and web server
  • Documentation quality is uneven across the newer parts of the platform
  • Smaller community than the most popular tracking tools, so fewer worked examples exist

Lightdash

  • Requires existing dbt infrastructure, not suitable for teams without data models
  • Enterprise features and AI agents unavailable in open-source MIT-licensed core

Pricing, plan by plan

ClearML

Free
  • Open sourceFree
    • Experiment tracking
    • Pipelines
    • Self-hosted server

Lightdash

Free
  • Open SourceFree
    • MIT-licensed core
    • Self-hostable
    • dbt integration
  • Cloud Managed$undefined/mo
    • Managed hosting
    • Premium features
    • AI agent capabilities

Which should you pick?

Choose ClearML if

  • You need experiment tracking.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes.
  • You also want remote execution.
ClearML review

Choose Lightdash if

  • You need dbt integration.
  • You want to start without paying.
  • You work on Web, Cloud (managed), Self-hosted (on-premise).
  • You also want metrics layer.
Lightdash review

Questions people ask

Is ClearML or Lightdash better?
Neither clearly leads. ClearML starts at Free and Lightdash at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClearML or Lightdash?
ClearML starts at Free and Lightdash at Free.
Does ClearML or Lightdash run on more platforms?
ClearML runs on Linux, macOS, Windows, Docker, Kubernetes. Lightdash runs on Web, Cloud (managed), Self-hosted (on-premise).
Can I use ClearML for free?
Both have a free tier, so you can try either at no cost before committing.
What is ClearML best used for?
ClearML is most often used for tracking experiments across a team so results are reproducible, moving training from laptops to shared gpu hardware without repackaging, versioning datasets alongside the experiments that consumed them. Of those, tracking experiments across a team so results are reproducible and moving training from laptops to shared gpu hardware without repackaging are not what Lightdash is typically brought in for.
What can ClearML do that Lightdash cannot?
ClearML covers Experiment tracking, Remote execution, Data versioning, Pipelines. Lightdash covers dbt Integration, Metrics Layer, Dashboards, Scheduling.

Answered from the vendors’ own pages

ClearML: Is ClearML free?

The open-source version is free and self-hostable. Hosted and enterprise tiers are paid.

Lightdash: Is Lightdash free?

Yes. Lightdash is free and open source under the MIT license. Self-hosting is completely free. Managed cloud services and enterprise features require separate licensing.

Source
ClearML: How much code does tracking require?

Very little — adding a couple of lines to an existing training script captures parameters, metrics and environment automatically.

Lightdash: How does Lightdash integrate with dbt?

Lightdash reads dbt models and metric definitions directly. A team defines metrics once in dbt and reuses them across dashboards, exploration, and AI agents without redefinition.

Source
ClearML: Does ClearML replace MLflow?

It covers MLflow’s tracking and adds orchestration, remote execution and data versioning. Whether that breadth is an advantage or extra weight depends on whether you need the rest.

Lightdash: Does Lightdash support SQL queries?

Yes. As a modern BI platform for analysts, Lightdash supports full SQL capabilities alongside dbt model exploration and visual query builders.

Source
Lightdash: What are Lightdash AI agents?

Lightdash AI agents, available on paid plans, allow natural language queries against your data, generating SQL and visualizations automatically from questions.

Source
Lightdash: Can Lightdash be self-hosted?

Yes. Lightdash's MIT-licensed core is completely self-hostable and free. Enterprise features and AI agents ship under separate licensing.

Source
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