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Databases · head to head

Immuta vs Ray

Immuta logo

Immuta

Databases

Attribute-based access control and masking applied inside Snowflake, Databricks and BigQuery

From
On request
Free plan
No
Visit ImmutaFull review
Ray logo

Ray

Machine Learning

Scale AI and Python applications

From
Free
Free plan
Yes
Visit RayFull review

The short version

  • Ray is free; Immuta prices on request.
  • Only Immuta lists attribute-based policy; only Ray lists distributed computing.
  • Where Ray falls short: windows support is beta and multi node Ray clusters are untested on Windows.
  • Prices and features on this page were last checked on 13 November 2026.

Where they differ

Only the attributes on which Immuta and Ray actually diverge.

Attributes where Immuta and Ray differ
AttributeImmutaRay
Starting priceOn requestFree
Pricing modelQuoteFreemium
Free tierNoYes
PlatformsWeb, APILinux, macOS, Windows
CategoryDatabasesMachine Learning

Not yet recorded: founded for Immuta.

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 Immuta

  • Attribute-based policy
  • Native enforcement
  • Dynamic masking
  • Row-level filtering
  • Purpose-based access
  • Sensitive data tagging
  • Audit logging
  • Multi-platform

Only in Ray

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

What people use each for

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

Immuta

  • A bank whose Snowflake estate has grown to tens of thousands of roles that no one can review before an auditnot Ray
  • A healthcare analytics team that must let researchers query patient data with identifiers masked unless a specific purpose is recordednot Ray
  • A multinational applying different residency and access rules per jurisdiction to the same tables without duplicating datasetsnot Ray
  • An organisation running both Snowflake and Databricks that wants one policy set rather than two divergent implementationsnot Ray

Ray

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

Where each one falls short

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

Immuta

  • Contracts commonly start around one hundred to two hundred thousand US dollars a year for mid-market deployments and exceed five hundred thousand at enterprise scale, which excludes most data teams without a regulatory mandate
  • Policy is only as good as the data classification underneath it, so an organisation with poorly tagged columns will spend months on classification before Immuta enforces anything useful
  • Native enforcement means capability varies by platform, and a feature available on Snowflake may be absent or behave differently on BigQuery, which undermines the promise of one policy set everywhere
  • Adding an access governance layer creates a new dependency in the path to data: a misconfigured policy silently returns fewer rows rather than erroring, and analysts can act on incomplete results without noticing
  • It governs cloud data platforms, so personal data in operational databases, files and SaaS applications sits outside its scope and needs separate controls, meaning Immuta is rarely the whole answer

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

Immuta

On request
  • Immuta PlatformOn request
    • Attribute-based policy authoring
    • Native enforcement in supported data platforms
    • Dynamic masking and row-level security

Ray

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

Which should you pick?

Choose Immuta if

  • You need attribute-based policy.
  • You work on Web, API.
  • You also want native enforcement.
Immuta review

Choose Ray if

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

Questions people ask

Is Immuta or Ray better?
Neither clearly leads. Immuta starts at On request and Ray at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Immuta or Ray?
Ray has a free tier; the other does not. Paid plans start at On request for Immuta and Free for Ray.
Does Immuta or Ray run on more platforms?
Immuta runs on Web, API. Ray runs on Linux, macOS, Windows.
Can I use Ray for free?
Yes. Ray has a free tier, so you can try it without paying. Immuta starts at On request.
What is Immuta best used for?
Immuta is most often used for a bank whose snowflake estate has grown to tens of thousands of roles that no one can review before an audit, a healthcare analytics team that must let researchers query patient data with identifiers masked unless a specific purpose is recorded, a multinational applying different residency and access rules per jurisdiction to the same tables without duplicating datasets, an organisation running both snowflake and databricks that wants one policy set rather than two divergent implementations. Of those, a bank whose snowflake estate has grown to tens of thousands of roles that no one can review before an audit and a healthcare analytics team that must let researchers query patient data with identifiers masked unless a specific purpose is recorded are not what Ray is typically brought in for.
What can Immuta do that Ray cannot?
Immuta covers Attribute-based policy, Native enforcement, Dynamic masking, Row-level filtering. Ray covers Distributed computing, Ray Train, Ray Tune, RLlib.

Answered from the vendors’ own pages

Immuta: Does Immuta sit in the query path?

No. It compiles policies into the data platform's own native controls, so queries run at normal speed through your existing tools.

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
Immuta: What does it cost?

Not published. Market data suggests roughly 100,000 to 200,000 US dollars a year for mid-market deployments and considerably more at enterprise scale.

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
Immuta: Is Immuta still independent?

Yes. It remains independently owned, unlike several competitors in data access governance that have been acquired.

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
Immuta: Does it work across more than one warehouse?

Yes, one policy set can target Snowflake, Databricks, BigQuery and Starburst, though enforcement capability varies by platform.

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