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Databases · head to head

Memcached vs Ray

M

Memcached

Databases

Distributed memory object caching system

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: Memcached no persistence at all: restart a node and its cache is gone, which every design must assume; Ray windows support is beta and multi node Ray clusters are untested on Windows
  • They diverge on capability: Memcached covers In-memory key-value cache, Ray covers Distributed computing.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Memcached and Ray actually diverge.

Attributes where Memcached and Ray differ
AttributeMemcachedRay
Pricing modelOpen source, no licence fee; managed cloud billed separatelyfreemium
PlatformsLinux, macOS, Windows, Docker, 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 Memcached

  • In-memory key-value cache
  • Multithreaded
  • Client-side sharding
  • Predictable memory use

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.

Memcached

  • Caching expensive database query results to cut loadnot Ray
  • Session storage where losing sessions on restart is acceptablenot Ray
  • Fronting an API whose responses are costly and change slowlynot Ray

Ray

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

Where each one falls short

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

Memcached

  • No persistence at all: restart a node and its cache is gone, which every design must assume
  • No replication or failover, so losing a node loses that share of the cache
  • Only simple key-value, with none of the lists, sorted sets or streams Redis offers
  • Values are capped at 1MB by default, which surprises teams caching large documents

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

Memcached

Free
  • MemcachedFree
    • Full functionality
    • Self-hosted
    • No usage limits

Ray

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

Which should you pick?

Choose Memcached if

  • You need in-memory key-value cache.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Self-hosted.
  • You also want multithreaded.
Memcached 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 Memcached or Ray better?
Neither clearly leads. Memcached 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, Memcached or Ray?
Memcached starts at Free and Ray at Free.
Does Memcached or Ray run on more platforms?
Memcached runs on Linux, macOS, Windows, Docker, Self-hosted. Ray runs on Linux, Mac, Windows.
Can I use Memcached for free?
Both have a free tier, so you can try either at no cost before committing.
What is Memcached best used for?
Memcached is most often used for caching expensive database query results to cut load, session storage where losing sessions on restart is acceptable, fronting an api whose responses are costly and change slowly. Of those, caching expensive database query results to cut load and session storage where losing sessions on restart is acceptable are not what Ray is typically brought in for.
What can Memcached do that Ray cannot?
Memcached covers In-memory key-value cache, Multithreaded, Client-side sharding, Predictable memory use. Ray covers Distributed computing, Ray Train, Ray Tune, RLlib.

Answered from the vendors’ own pages

Memcached: Is Memcached free?

Yes, open source with no licence fee.

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
Memcached: Memcached or Redis?

Memcached is a pure cache: simpler, multithreaded and very predictable. Redis adds persistence, replication and rich data structures, which is why it is the default choice unless you specifically want a cache and nothing more.

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
Memcached: Does Memcached persist data?

No. Everything is in memory and lost on restart, by design.

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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