Machine Learning · head to head
ClearML vs Orange

ClearML
Machine Learning
Open-source MLOps platform for experiment tracking and orchestration
- From
- Free
- Rated
- -
The short version
- Each has a real cost: ClearML broad scope means more to learn and more to run than a focused tracking tool; Orange orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
- They diverge on capability: ClearML covers Experiment tracking, Orange covers Visual programming.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which ClearML and Orange actually diverge.
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 Orange
- Visual programming
- Data visualization
- Machine learning
- Text mining
- Bioinformatics
- Python
- scikit-learn
- PyQt
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 Orange
- Moving training from laptops to shared GPU hardware without repackagingnot Orange
- Versioning datasets alongside the experiments that consumed themnot Orange
Orange
- Visual programming for data mining and machine learning workflowsnot ClearML
- Teaching data science without writing codenot ClearML
- Exploratory data visualisation and clustering on tabular datanot 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
Orange
- Orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
- The widgets and canvas are built on Qt, which is itself distributed under GPL 3.0
- Orange add-ons may carry additional licensing requirements set in their own licence files
- Documentation and website content are under Creative Commons Attribution-ShareAlike, which imposes an attribution and share-alike obligation on reuse
- The software is distributed without any warranty of merchantability or fitness for a particular purpose
Pricing, plan by plan
ClearML
Free- Open sourceFree
- Experiment tracking
- Pipelines
- Self-hosted server
Orange
Free- Open SourceFree
- Visual programming
- Machine learning
- Data visualization
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.
Choose Orange if
- You need visual programming.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want data visualization.
Questions people ask
- Is ClearML or Orange better?
- Neither clearly leads. ClearML starts at Free and Orange at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, ClearML or Orange?
- ClearML starts at Free and Orange at Free.
- Does ClearML or Orange run on more platforms?
- ClearML runs on Linux, macOS, Windows, Docker, Kubernetes. Orange runs on Linux, Mac, Windows.
- 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 Orange is typically brought in for.
- What can ClearML do that Orange cannot?
- ClearML covers Experiment tracking, Remote execution, Data versioning, Pipelines. Orange covers Visual programming, Data visualization, Machine learning, Text mining.
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.
Orange: What is the cost of Orange Data Mining?
Orange Data Mining is free open-source software available for Windows, Mac, and other platforms. There are no subscription fees, licensing costs, or paid tiers.
SourceClearML: How much code does tracking require?
Very little — adding a couple of lines to an existing training script captures parameters, metrics and environment automatically.
Orange: How is Orange Data Mining funded?
Orange Data Mining is supported through optional voluntary donations. The project encourages donations from users who value the software to support bug fixes, new features, educational content, and infrastructure maintenance.
SourceClearML: 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.
Related pages
Other head to heads
- ClearML vs MLflow
- ClearML vs Weights & Biases
- ClearML vs Comet ML
- ClearML vs Neptune.ai
- ClearML vs Dataiku
- ClearML vs Pachyderm
- ClearML vs Azure Machine Learning
- ClearML vs Domino Data Lab
- ClearML vs DVC
- ClearML vs AWS SageMaker
- ClearML vs Google Vertex AI
- ClearML vs DataRobot
- ClearML vs Pinecone
- ClearML vs Python
- ClearML vs PyTorch
- ClearML vs scikit-learn
- ClearML vs Apache Spark MLlib
- ClearML vs Weaviate
- ClearML vs Weka
- ClearML vs MATLAB
- ClearML vs KNIME
- ClearML vs Jupyter
- ClearML vs Alteryx
- ClearML vs JMP
- ClearML vs RapidMiner
- ClearML vs Dask
- ClearML vs Fal AI
- ClearML vs Groq
- ClearML vs Haystack
- ClearML vs IBM SPSS
- Orange vs MLflow
- Orange vs Weights & Biases
- Orange vs Comet ML
- Orange vs Neptune.ai
- Orange vs Dataiku
- Orange vs Pachyderm
- Orange vs Azure Machine Learning
- Orange vs Domino Data Lab
- Orange vs DVC
- Orange vs AWS SageMaker
- Orange vs Google Vertex AI
- Orange vs DataRobot
- Orange vs Pinecone
- Orange vs Python
- Orange vs PyTorch
- Orange vs scikit-learn
- Orange vs Apache Spark MLlib
- Orange vs Weaviate
- Orange vs Weka
- Orange vs MATLAB
- Orange vs KNIME
- Orange vs Jupyter
- Orange vs Alteryx
- Orange vs JMP
- Orange vs RapidMiner
- Orange vs Dask
- Orange vs Fal AI
- Orange vs Groq
- Orange vs Haystack
- Orange vs IBM SPSS

