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Machine Learning · head to head

Ray vs SAS

Ray logo

Ray

Machine Learning

Scale AI and Python applications

From
Free
Rated
-
Full reviewWebsite
SAS logo

SAS

Machine Learning

Analytics, AI and data management software

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Ray windows support is beta and multi node Ray clusters are untested on Windows; SAS sAS publishes no rate, no minimum and no named cost driver; the how to buy page offers only a customized price quote based on your requirements and deployment preferences
  • They diverge on capability: Ray covers Distributed computing, SAS covers Statistical analysis.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Ray and SAS actually diverge.

Attributes where Ray and SAS differ
AttributeRaySAS
Pricing modelfreemiumsubscription
PlatformsLinux, Mac, WindowsLinux, Windows, Web
Founded20191976

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 Ray

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

Only in SAS

  • Statistical analysis
  • Machine learning
  • Forecasting
  • Text analytics
  • Optimization
  • Python
  • R
  • Hadoop

Both cover

  • Linux support
  • Windows support

What people use each for

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

Ray

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

SAS

  • Regulated statistical analysis and clinical reportingnot Ray
  • Enterprise data management, visualization and decisioning on one licensed platformnot Ray

Where each one falls short

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

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

SAS

  • SAS publishes no rate, no minimum and no named cost driver; the how to buy page offers only a customized price quote based on your requirements and deployment preferences
  • Most new and existing customers are routed through authorized resellers rather than buying direct
  • Cloud marketplace purchases require choosing between pay as you go and bring your own licence, each with different licensing terms

Pricing, plan by plan

Ray

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

SAS

Free
  • SAS OnDemand for AcademicsFree
    • Academic use
    • Core SAS
  • SAS ViyaFree
    • Full platform
    • Cloud-native
    • AI/ML

Which should you pick?

Choose Ray if

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

Choose SAS if

  • You need statistical analysis.
  • You want to start without paying.
  • You work on Linux, Windows, Web.
  • You also want machine learning.
SAS review

Questions people ask

Is Ray or SAS better?
Neither clearly leads. Ray starts at Free and SAS at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Ray or SAS?
Ray starts at Free and SAS at Free.
Does Ray or SAS run on more platforms?
Ray runs on Linux, Mac, Windows. SAS runs on Linux, Windows, Web.
Can I use Ray for free?
Both have a free tier, so you can try either at no cost before committing.
What is Ray best used for?
Ray is most often used for distributed ai model training and serving, large-scale data processing, reinforcement learning workloads, ml inference serving. Of those, distributed ai model training and serving and large-scale data processing are not what SAS is typically brought in for.
What can Ray do that SAS cannot?
Ray covers Distributed computing, Ray Train, Ray Tune, RLlib. SAS covers Statistical analysis, Machine learning, Forecasting, Text analytics. Both handle Linux support, Windows support.

Answered from the vendors’ own pages

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
SAS: Does SAS offer a free trial?

Yes, SAS offers a free trial through a private trial environment for SAS Viya. Interested customers can request access by submitting a trial form on their website.

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
SAS: How does SAS price its software?

SAS does not publish standard pricing on its website. Instead, it uses a custom enterprise sales model where customers can choose between paying as-you-go or purchasing SAS Viya Enterprise. Specific pricing must be requested directly from their sales team.

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
SAS: What are my pricing options?

SAS offers flexible purchasing models including pay-as-you-go and enterprise licensing options. The company states they can help you find the environment that fits your needs, but specific terms must be discussed with sales.

Source
SAS: How do I get a pricing quote?

You can request pricing through their website by using the quote request form, requesting a customized demo, or contacting their sales team directly.

Source
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