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Machine Learning · head to head

ClearML vs H2O.ai

ClearML logo

ClearML

Machine Learning

Open-source MLOps platform for experiment tracking and orchestration

From
Free
Rated
-
Full reviewWebsite
H2O.ai logo

H2O.ai

Machine Learning

AI Cloud for building and deploying AI applications

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; H2O.ai java is always required to run H2O-3 even when working from R or Python, and only a 64-bit JRE or JDK is supported
  • They diverge on capability: ClearML covers Experiment tracking, H2O.ai covers AutoML.

Where they differ

Only the attributes on which ClearML and H2O.ai actually diverge.

Attributes where ClearML and H2O.ai differ
AttributeClearMLH2O.ai
Pricing modelOpen-source self-hosted, with paid hosted and enterprise tiersfreemium
PlatformsLinux, macOS, Windows, Docker, KubernetesWeb, Cloud
FoundedUnknown2011

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 H2O.ai

  • AutoML
  • Distributed computing
  • Feature engineering
  • Model explainability
  • Time series forecasting
  • Spark
  • Hadoop
  • Python

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 H2O.ai
  • Moving training from laptops to shared GPU hardware without repackagingnot H2O.ai
  • Versioning datasets alongside the experiments that consumed themnot H2O.ai

H2O.ai

  • Distributed in-memory machine learning over large datasetsnot ClearML
  • Training and productionising models from R or Python against a shared H2O clusternot 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

H2O.ai

  • Java is always required to run H2O-3 even when working from R or Python, and only a 64-bit JRE or JDK is supported
  • Supported Java versions stop at Java SE 17; newer versions only run by forcing an unsupported version flag and are guaranteed for experiments rather than production
  • H2O-3 only supports numpy below version 2, so a numpy 2 environment must be downgraded
  • Supported Python versions are limited to 3.7 through 3.11
  • The Flow web UI requires an internet browser and is the only graphical interface

Pricing, plan by plan

ClearML

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

H2O.ai

Free
  • H2O-3 Open SourceFree
    • Core algorithms
    • AutoML
    • Community support
  • Driverless AIFree
    • Automatic feature engineering
    • Model explainability
    • Enterprise support

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 H2O.ai if

  • You need automl.
  • You want to start without paying.
  • You work on Web, Cloud.
  • You also want distributed computing.
H2O.ai review

Questions people ask

Is ClearML or H2O.ai better?
Neither clearly leads. ClearML starts at Free and H2O.ai at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClearML or H2O.ai?
ClearML starts at Free and H2O.ai at Free.
Does ClearML or H2O.ai run on more platforms?
ClearML runs on Linux, macOS, Windows, Docker, Kubernetes. H2O.ai runs on Web, Cloud.
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 H2O.ai is typically brought in for.
What can ClearML do that H2O.ai cannot?
ClearML covers Experiment tracking, Remote execution, Data versioning, Pipelines. H2O.ai covers AutoML, Distributed computing, Feature engineering, Model explainability.

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.

H2O.ai: Is H2O open source and free?

Yes. H2O-3 OSS is free and Apache-licensed, designed for self-managed and experimental workflows. H2O.ai also offers enterprise cloud solutions with additional features.

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.

H2O.ai: How many companies use H2O's open source platform?

Over 18,000 companies across Finance, Insurance, Healthcare, Retail, Telco, Sales, and Marketing use H2O's open-source machine learning platform.

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.

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