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Databases · head to head

Apache Pulsar vs Ray

Apache Pulsar logo

Apache Pulsar

Databases

Cloud-native messaging and streaming with separated storage

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: Apache Pulsar more components than Kafka: brokers, BookKeeper and ZooKeeper each need operating; Ray windows support is beta and multi node Ray clusters are untested on Windows
  • They diverge on capability: Apache Pulsar covers Separated storage, Ray covers Distributed computing.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Apache Pulsar and Ray actually diverge.

Attributes where Apache Pulsar and Ray differ
AttributeApache PulsarRay
Pricing modelOpen source, no licence feefreemium
PlatformsLinux, Docker, Kubernetes, Self-hostedLinux, 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 Apache Pulsar

  • Separated storage
  • Queuing and streaming
  • Built-in multi-tenancy
  • Geo-replication

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.

Apache Pulsar

  • Platforms needing both work queues and replayable streams without running two systemsnot Ray
  • Multi-tenant messaging where isolation between teams is a requirementnot Ray
  • Deployments where storage and traffic grow at genuinely different ratesnot Ray

Ray

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

Where each one falls short

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

Apache Pulsar

  • More components than Kafka: brokers, BookKeeper and ZooKeeper each need operating
  • Correspondingly harder to run well, and the expertise is rarer than Kafka expertise
  • A much smaller ecosystem of connectors, tooling and hiring pool than Kafka
  • The architectural advantages only pay off at a scale most deployments never reach

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

Apache Pulsar

Free
  • Apache PulsarFree
    • Full functionality
    • No usage limits
    • Community support

Ray

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

Which should you pick?

Choose Apache Pulsar if

  • You need separated storage.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want queuing and streaming.
Apache Pulsar 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 Apache Pulsar or Ray better?
Neither clearly leads. Apache Pulsar 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, Apache Pulsar or Ray?
Apache Pulsar starts at Free and Ray at Free.
Does Apache Pulsar or Ray run on more platforms?
Apache Pulsar runs on Linux, Docker, Kubernetes, Self-hosted. Ray runs on Linux, Mac, Windows.
Can I use Apache Pulsar for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Pulsar best used for?
Apache Pulsar is most often used for platforms needing both work queues and replayable streams without running two systems, multi-tenant messaging where isolation between teams is a requirement, deployments where storage and traffic grow at genuinely different rates. Of those, platforms needing both work queues and replayable streams without running two systems and multi-tenant messaging where isolation between teams is a requirement are not what Ray is typically brought in for.
What can Apache Pulsar do that Ray cannot?
Apache Pulsar covers Separated storage, Queuing and streaming, Built-in multi-tenancy, Geo-replication. Ray covers Distributed computing, Ray Train, Ray Tune, RLlib.

Answered from the vendors’ own pages

Apache Pulsar: Is Apache Pulsar free?

Yes, open source under the Apache Software Foundation.

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
Apache Pulsar: Pulsar or Kafka?

Pulsar separates storage from compute and covers queuing and streaming in one system. Kafka has a far larger ecosystem and hiring pool. Most teams should have a specific reason before choosing Pulsar.

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
Apache Pulsar: Why does separated storage matter?

Brokers hold no data, so adding or replacing one requires no rebalancing, and storage can grow without adding serving capacity.

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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