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Machine Learning · head to head

ClearML vs Domino Data Lab

ClearML logo

ClearML

Machine Learning

Open-source MLOps platform for experiment tracking and orchestration

From
Free
Rated
-
Full reviewWebsite
Domino Data Lab logo

Domino Data Lab

Machine Learning

Enterprise MLOps platform

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; Domino Data Lab pricing is by quote only: the pricing page publishes no rate and no minimum, and the tier breakdown is behind a downloadable datasheet form
  • They diverge on capability: ClearML covers Experiment tracking, Domino Data Lab covers Reproducible environments.

Where they differ

Only the attributes on which ClearML and Domino Data Lab actually diverge.

Attributes where ClearML and Domino Data Lab differ
AttributeClearMLDomino Data Lab
Pricing modelOpen-source self-hosted, with paid hosted and enterprise tierssubscription
PlatformsLinux, macOS, Windows, Docker, KubernetesWeb
FoundedUnknown2013

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

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 Domino Data Lab

  • Reproducible environments
  • Model registry
  • Model monitoring
  • Collaboration
  • Governance
  • AWS
  • Azure
  • GCP

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 Domino Data Lab
  • Moving training from laptops to shared GPU hardware without repackagingnot Domino Data Lab
  • Versioning datasets alongside the experiments that consumed themnot Domino Data Lab

Domino Data Lab

  • Running reproducible data science workspaces and experiments on shared computenot ClearML
  • Deploying and monitoring models with governance controlsnot ClearML
  • Giving regulated enterprises a self managed MLOps platformnot 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

Domino Data Lab

  • Pricing is by quote only: the pricing page publishes no rate and no minimum, and the tier breakdown is behind a downloadable datasheet form
  • Licensing is split by user type, with separate data science professional, data analyst, service account and admin licences
  • FinOps, Nexus and Governance are paid add on modules rather than part of the platform
  • Support level is a separate priced choice
  • Self managed VPC or on premises deployment requires the Premium tier or higher
  • No free trial is offered on the pricing page

Pricing, plan by plan

ClearML

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

Domino Data Lab

Free
  • TrialFree
    • 14-day trial
    • Full features
  • EnterpriseFree
    • Full platform
    • Enterprise support
    • SLA

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 Domino Data Lab if

  • You need reproducible environments.
  • You want to start without paying.
  • You also want model registry.
Domino Data Lab review

Questions people ask

Is ClearML or Domino Data Lab better?
Neither clearly leads. ClearML starts at Free and Domino Data Lab at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClearML or Domino Data Lab?
ClearML starts at Free and Domino Data Lab at Free.
Does ClearML or Domino Data Lab run on more platforms?
ClearML runs on Linux, macOS, Windows, Docker, Kubernetes. Domino Data Lab runs on Web.
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 Domino Data Lab is typically brought in for.
What can ClearML do that Domino Data Lab cannot?
ClearML covers Experiment tracking, Remote execution, Data versioning, Pipelines. Domino Data Lab covers Reproducible environments, Model registry, Model monitoring, Collaboration.

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.

Domino Data Lab: What user license types are available and what can they do?

Data Science Professionals get full development, model training, and GPU access. Data Analysts get Python/R environments and dashboard creation with limited computing. License counts vary by tier (5-10 admin licenses and 5-10 service accounts).

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.

Domino Data Lab: What support response times are included?

Premium tier includes 2-business-day SLA for support. Enterprise includes 1-business-day SLA plus 24/7 support for critical issues. Both tiers include monitoring and support services.

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.

Domino Data Lab: Are there additional modules available beyond the base subscription?

Yes, advanced add-on modules are available including FinOps (cost optimization), Nexus (hybrid/multicloud support), and Governance. These require separate purchase on top of your subscription tier.

Source
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