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Machine Learning · head to head

Databricks vs Ray

Databricks logo

Databricks

Machine Learning

Unified analytics platform for data engineering and data science

From
Free
Rated
-
Full reviewWebsite
Ray logo

Ray

Machine Learning

Scale AI and Python applications

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges; Ray windows support is beta and multi node Ray clusters are untested on Windows
  • They diverge on capability: Databricks covers Delta Lake, Ray covers Distributed computing.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Databricks and Ray actually diverge.

Attributes where Databricks and Ray differ
AttributeDatabricksRay
Pricing modelusage-basedfreemium
PlatformsWeb, Aws, Azure, GcpLinux, Mac, Windows
Founded20132019

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 Databricks

  • Delta Lake
  • Apache Spark
  • MLflow
  • Unity Catalog
  • Photon Engine
  • Collaborative Notebooks
  • Auto-scaling
  • AWS

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.

Databricks

  • Running Spark data engineering pipelines on managed clustersnot Ray
  • Building a lakehouse over data in cloud object storagenot Ray
  • Training and serving machine learning models alongside the datanot Ray

Ray

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

Where each one falls short

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

Databricks

  • Cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
  • The free trial lasts 14 days
  • Discounts require a Committed Use Contract, with larger commitments needed for larger discounts
  • Azure Databricks pricing is set by Microsoft rather than by Databricks
  • Security and compliance capabilities are sold as separate platform add ons rather than included in the base rate

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

Databricks

Free
  • Community EditionFree
    • Limited cluster
    • Notebook environment
    • Community support
  • Standard$0.07/DBU
    • Jobs compute
    • SQL compute
    • Standard support

Ray

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

Which should you pick?

Choose Databricks if

  • You need delta lake.
  • You want to start without paying.
  • You work on Web, Aws, Azure, Gcp.
  • You also want apache spark.
Databricks review

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

Questions people ask

Is Databricks or Ray better?
Neither clearly leads. Databricks 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, Databricks or Ray?
Databricks starts at Free and Ray at Free.
Does Databricks or Ray run on more platforms?
Databricks runs on Web, Aws, Azure, Gcp. Ray runs on Linux, Mac, Windows.
Can I use Databricks for free?
Both have a free tier, so you can try either at no cost before committing.
What is Databricks best used for?
Databricks is most often used for running spark data engineering pipelines on managed clusters, building a lakehouse over data in cloud object storage, training and serving machine learning models alongside the data. Of those, running spark data engineering pipelines on managed clusters and building a lakehouse over data in cloud object storage are not what Ray is typically brought in for.
What can Databricks do that Ray cannot?
Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Ray covers Distributed computing, Ray Train, Ray Tune, RLlib.

Answered from the vendors’ own pages

Databricks: How is Databricks priced?

Databricks bills pay as you go with no up front cost, charging per second for the products used. Consumption is measured in Databricks Units, a normalised unit of processing power on the platform.

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
Databricks: Does Databricks publish a per DBU price?

Not on its main pricing page. Rates vary by product and instance type, and Databricks directs buyers to individual product pricing pages and a calculator rather than listing a single figure.

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
Databricks: Does the Databricks price include cloud costs?

No. Databricks states that if you configure it to work with your own cloud account, your cloud provider still charges you separately for the underlying resources.

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
Databricks: Can I get a discount on Databricks?

Databricks offers Committed Use Contracts, where larger usage commitments earn greater benefits, including options to use commitments flexibly across multiple clouds.

Source
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