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Machine Learning · head to head

Orange vs Ray

Orange logo

Orange

Machine Learning

Data mining and visualization toolkit

From
Free
Rated
-
Ray logo

Ray

Machine Learning

Scale AI and Python applications

From
Free
Rated
-

The short version

  • Each has a real cost: 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; Ray windows support is beta and multi node Ray clusters are untested on Windows
  • They diverge on capability: Orange covers Visual programming, Ray covers Distributed computing.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Orange and Ray actually diverge.

Attributes where Orange and Ray differ
AttributeOrangeRay
Pricing modelopen-sourcefreemium
Founded19962019

Identical on both: starting price (Free), free tier (Yes), platforms (Linux, Mac, Windows), 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 Orange

  • Visual programming
  • Data visualization
  • Machine learning
  • Text mining
  • Bioinformatics
  • Python
  • PyQt

Only in Ray

  • Distributed computing
  • Ray Train
  • Ray Tune
  • RLlib
  • Ray Serve
  • PyTorch
  • TensorFlow
  • Hugging Face

Both cover

  • scikit-learn
  • Linux support
  • Mac support
  • Windows support

What people use each for

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

Orange

  • Visual programming for data mining and machine learning workflowsnot Ray
  • Teaching data science without writing codenot Ray
  • Exploratory data visualisation and clustering on tabular datanot Ray

Ray

  • Distributed AI model training and servingnot Orange
  • Large-scale data processingnot Orange
  • Reinforcement learning workloadsnot Orange
  • ML inference servingnot Orange

Where each one falls short

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

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

Ray

  • Windows support is beta and multi node Ray clusters are untested on Windows
  • Windows lacks copy on write forking, which raises memory requirements, and Ray code assumes UNIX filenames
  • Multi node clusters are untested on Apple Silicon Macs
  • The Java API is experimental and community supported only, and requires matching Java and Python versions
  • Python 3.13 support is beta

Pricing, plan by plan

Orange

Free
  • Open SourceFree
    • Visual programming
    • Machine learning
    • Data visualization

Ray

Free
  • Open SourceFree
    • Full Ray framework
    • All libraries
    • Community support
  • Anyscale PlatformFree
    • Managed infrastructure
    • Enterprise support
    • SLAs

Which should you pick?

Choose Orange if

  • You need visual programming.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want data visualization.

Choose Ray if

  • You need distributed computing.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want ray train.

Questions people ask

Is Orange or Ray better?
Neither clearly leads. Orange starts at Free and Ray at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Orange or Ray?
Orange starts at Free and Ray at Free.
Does Orange or Ray run on more platforms?
Both run on Linux, Mac, Windows, so platform support will not decide this one for you.
Can I use Orange for free?
Both have a free tier, so you can try either at no cost before committing.
What is Orange best used for?
Orange is most often used for visual programming for data mining and machine learning workflows, teaching data science without writing code, exploratory data visualisation and clustering on tabular data. Of those, visual programming for data mining and machine learning workflows and teaching data science without writing code are not what Ray is typically brought in for.
What can Orange do that Ray cannot?
Orange covers Visual programming, Data visualization, Machine learning, Text mining. Ray covers Distributed computing, Ray Train, Ray Tune, RLlib. Both handle scikit-learn, Linux support, Mac support, Windows support.

Answered from the vendors’ own pages

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.

Source
Ray: Is Ray free?

Yes. Ray is free and open source software with over 34,800 GitHub stars and 1,000+ contributors. Users can download and use the Ray framework at no cost.

Source
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.

Source
Ray: Is there a paid option for Ray?

Yes. Anyscale, the managed platform built by Ray's creators, offers paid tiers with enterprise features like governance and advanced tooling. Specific Anyscale pricing details are not listed on the Ray website.

Source
Ray: Can I try Ray with credits?

Yes. New users can try Ray with $100 credit on Anyscale's managed platform to explore the service.

Source
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