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Databases · head to head

Presto vs Ray

Presto logo

Presto

Databases

The Meta-lineage distributed SQL query engine, distinct from the Trino fork

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: Presto the original creators and most of the active contributor base left for Trino in 2020, so Presto has the smaller community, fewer connectors and slower feature delivery of the two branches.; Ray windows support is beta and multi node Ray clusters are untested on Windows
  • They diverge on capability: Presto covers Federated querying, Ray covers Distributed computing.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Presto and Ray actually diverge.

Attributes where Presto and Ray differ
AttributePrestoRay
Pricing modelOpen source, no licence feefreemium
PlatformsLinux, Docker, KubernetesLinux, Mac, Windows
CategoryDatabasesMachine Learning
FoundedUnknown2019

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

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 Presto

  • Federated querying
  • In-memory execution
  • Open table format support
  • Presto C++ workers
  • ANSI SQL
  • Pluggable connectors

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.

Presto

  • An existing PrestoDB estate that needs continued upgrades rather than a migration to Trinonot Ray
  • A team buying IBM watsonx.data, where Presto is the underlying query enginenot Ray
  • Joining a Hive or Iceberg lake to an operational PostgreSQL database in one query without an ETL stepnot Ray
  • Very large scale interactive SQL where the Meta-tested branch is a specific requirementnot Ray

Ray

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

Where each one falls short

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

Presto

  • The original creators and most of the active contributor base left for Trino in 2020, so Presto has the smaller community, fewer connectors and slower feature delivery of the two branches.
  • Documentation, tutorials and Stack Overflow answers for the two projects are frequently mixed up, and a solution written for Trino often does not apply, which costs real debugging time.
  • It is a query engine with no storage of its own, so query performance is dictated by your file layout, partitioning and statistics, and a badly organised lake makes Presto look slow.
  • Memory-bound execution means a single large join can fail the whole query rather than spilling gracefully, and tuning cluster memory settings is a persistent operational chore.
  • Commercial support has consolidated into IBM since the Ahana acquisition, so the independent vendor market that once existed around Presto is largely gone.

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

Presto

Free
  • PrestoFree
    • Apache 2.0 licence
    • Presto Foundation governance under the Linux Foundation
    • No node or query limits

Ray

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

Which should you pick?

Choose Presto if

  • You need federated querying.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes.
  • You also want in-memory execution.
Presto 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 Presto or Ray better?
Neither clearly leads. Presto 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, Presto or Ray?
Presto starts at Free and Ray at Free.
Does Presto or Ray run on more platforms?
Presto runs on Linux, Docker, Kubernetes. Ray runs on Linux, Mac, Windows.
Can I use Presto for free?
Both have a free tier, so you can try either at no cost before committing.
What is Presto best used for?
Presto is most often used for an existing prestodb estate that needs continued upgrades rather than a migration to trino, a team buying ibm watsonx.data, where presto is the underlying query engine, joining a hive or iceberg lake to an operational postgresql database in one query without an etl step, very large scale interactive sql where the meta-tested branch is a specific requirement. Of those, an existing prestodb estate that needs continued upgrades rather than a migration to trino and a team buying ibm watsonx.data, where presto is the underlying query engine are not what Ray is typically brought in for.
What can Presto do that Ray cannot?
Presto covers Federated querying, In-memory execution, Open table format support, Presto C++ workers. Ray covers Distributed computing, Ray Train, Ray Tune, RLlib.

Answered from the vendors’ own pages

Presto: Is this Presto or Trino?

This is PrestoDB, the branch that stayed at Facebook and moved to the Linux Foundation. Trino is the 2020 fork by the original creators.

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
Presto: Which should I choose for a new project?

Trino, in most cases. It has the larger community, more connectors and more commercial options.

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
Presto: Who maintains Presto now?

Principally Meta, Uber and IBM, which acquired the Presto vendor Ahana in 2023.

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
Presto: Is it still actively released?

Yes, releases continue on a regular cadence under the Presto Foundation.

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