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Machine Learning · head to head

ClearML vs OpenSearch

ClearML logo

ClearML

Machine Learning

Open-source MLOps platform for experiment tracking and orchestration

From
Free
Rated
-
Full reviewWebsite
OpenSearch logo

OpenSearch

Databases

Open-source search and analytics suite forked from Elasticsearch

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; OpenSearch diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
  • They diverge on capability: ClearML covers Experiment tracking, OpenSearch covers Full-text search.
  • Prices and features above were last checked on 29 August 2026.

Where they differ

Only the attributes on which ClearML and OpenSearch actually diverge.

Attributes where ClearML and OpenSearch differ
AttributeClearMLOpenSearch
Pricing modelOpen-source self-hosted, with paid hosted and enterprise tiersOpen source, no licence fee; managed services billed separately
PlatformsLinux, macOS, Windows, Docker, KubernetesLinux, Docker, Kubernetes, Self-hosted
CategoryMachine LearningDatabases

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 OpenSearch

  • Full-text search
  • OpenSearch Dashboards
  • Log analytics
  • Vector search

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

OpenSearch

  • Log and observability storage where an Apache-2.0 licence is a requirementnot ClearML
  • Replacing Elasticsearch after the licence change without changing architecturenot ClearML
  • Search plus analytics on one cluster rather than two systemsnot 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

OpenSearch

  • Diverged from Elasticsearch since 7.10, so clients, plugins and features no longer map one to one
  • Operationally heavy in the way Elasticsearch is: cluster sizing, shard strategy and JVM tuning are ongoing work
  • Smaller ecosystem of third-party tooling than Elasticsearch, which most integrations still target first
  • Overkill for plain application search, where a dedicated search engine is far simpler

Pricing, plan by plan

ClearML

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

OpenSearch

Free
  • OpenSearchFree
    • Full functionality
    • Self-hosted
    • No usage limits

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 OpenSearch if

  • You need full-text search.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want opensearch dashboards.
OpenSearch review

Questions people ask

Is ClearML or OpenSearch better?
Neither clearly leads. ClearML starts at Free and OpenSearch at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClearML or OpenSearch?
ClearML starts at Free and OpenSearch at Free.
Does ClearML or OpenSearch run on more platforms?
ClearML runs on Linux, macOS, Windows, Docker, Kubernetes. OpenSearch runs on Linux, Docker, Kubernetes, Self-hosted.
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 OpenSearch is typically brought in for.
What can ClearML do that OpenSearch cannot?
ClearML covers Experiment tracking, Remote execution, Data versioning, Pipelines. OpenSearch covers Full-text search, OpenSearch Dashboards, Log analytics, Vector search.

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.

OpenSearch: Is OpenSearch free?

Yes, Apache 2.0 licensed under the Linux Foundation. Amazon OpenSearch Service is a paid managed option.

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.

OpenSearch: Why does OpenSearch exist?

Elastic moved Elasticsearch off the Apache 2.0 licence in 2021. AWS forked the last Apache-licensed version, and the project now sits under the Linux Foundation.

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.

OpenSearch: Is OpenSearch compatible with Elasticsearch?

It was at the 7.10 fork point. Both have developed independently since, so compatibility weakens with every release and should be verified for the features you use.

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