File Storage · head to head
Ceph vs Ray
Ceph
File Storage
Open source distributed storage providing object, block and file from one cluster
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Ceph ceph assumes an operator who understands placement groups, CRUSH rules and recovery tuning, so organisations without dedicated storage staff routinely end up with a cluster that works until the first failure and then does not.; Ray windows support is beta and multi node Ray clusters are untested on Windows
- They diverge on capability: Ceph covers RADOS object store, Ray covers Distributed computing.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Ceph and Ray actually diverge.
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 Ceph
- RADOS object store
- RADOS Gateway
- RBD block devices
- CephFS
- CRUSH placement
- Erasure coded pools
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.
Ceph
- Backing a private cloud where virtual machine disks, shared filesystems and an S3 endpoint all need the same hardwarenot Ray
- Growing past the point where a proprietary array upgrade costs more than a rack of commodity serversnot Ray
- Research and media environments with petabytes of data and staff who can operate storagenot Ray
- Providing an S3 endpoint on premises with multi site replication under your own controlnot Ray
Ray
- Distributed AI model training and servingnot Ceph
- Large-scale data processingnot Ceph
- Reinforcement learning workloadsnot Ceph
- ML inference servingnot Ceph
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Ceph
- Ceph assumes an operator who understands placement groups, CRUSH rules and recovery tuning, so organisations without dedicated storage staff routinely end up with a cluster that works until the first failure and then does not.
- Small clusters are inefficient: three way replication means a third of raw capacity is usable, and erasure coding needs enough failure domains to be safe, so the economics only work above a certain size.
- Recovery and rebalancing generate heavy internal traffic, so a failed disk can degrade client latency across the cluster unless backfill is throttled correctly beforehand.
- Upgrades must follow a strict daemon order across monitors, managers, OSDs and gateways, and a mistake in that order on a live cluster is difficult to reverse.
- Because it is self hosted, every byte served to the internet is transit you pay for on your own links, so the free licence does not mean free egress and bandwidth planning becomes your problem rather than the providers.
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
Ceph
Free- CephFree
- Full functionality, no capacity limit
- Object, block and file interfaces
- Community support via mailing list and Slack
Ray
Free- Open SourceFree
- Full Ray framework
- All libraries
- Community support
- Anyscale PlatformFree
- Managed infrastructure
- Enterprise support
- SLAs
Which should you pick?
Choose Ceph if
- You need rados object store.
- You want to start without paying.
- You work on Linux.
- You also want rados gateway.
Choose Ray if
- You need distributed computing.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want ray train.
Questions people ask
- Is Ceph or Ray better?
- Neither clearly leads. Ceph 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, Ceph or Ray?
- Ceph starts at Free and Ray at Free.
- Does Ceph or Ray run on more platforms?
- Ceph runs on Linux. Ray runs on Linux, Mac, Windows.
- Can I use Ceph for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Ceph best used for?
- Ceph is most often used for backing a private cloud where virtual machine disks, shared filesystems and an s3 endpoint all need the same hardware, growing past the point where a proprietary array upgrade costs more than a rack of commodity servers, research and media environments with petabytes of data and staff who can operate storage, providing an s3 endpoint on premises with multi site replication under your own control. Of those, backing a private cloud where virtual machine disks, shared filesystems and an s3 endpoint all need the same hardware and growing past the point where a proprietary array upgrade costs more than a rack of commodity servers are not what Ray is typically brought in for.
- What can Ceph do that Ray cannot?
- Ceph covers RADOS object store, RADOS Gateway, RBD block devices, CephFS. Ray covers Distributed computing, Ray Train, Ray Tune, RLlib.
Answered from the vendors’ own pages
Ceph: How many nodes do I need to start?
Three is the practical minimum for a replicated cluster with real fault tolerance, and most production advice starts at five once you account for maintenance windows.
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.
SourceCeph: Is it faster than a SAN?
Not on single stream latency. It wins on aggregate throughput and on growing without a forklift upgrade, which is a different property from raw speed.
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.
SourceCeph: Can I buy support?
Yes. IBM sells IBM Storage Ceph and SUSE and others have offered supported builds; the upstream project itself is free.
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.
SourceCeph: Should I use it just for S3?
If object is all you need, a dedicated object store is simpler to run. Ceph earns its complexity when you need block and file as well.
Related pages
Other head to heads
- Ceph vs MinIO
- Ceph vs Panzura
- Ceph vs Scality RING
- Ceph vs VAST Data
- Ceph vs Backblaze
- Ceph vs Duplicati
- Ceph vs Storj
- Ceph vs Tigris
- Ceph vs Cloudflare R2
- Ceph vs Cloudian
- Ceph vs IDrive e2
- Ceph vs TrueNAS
- Ceph vs LucidLink
- Ceph vs pCloud
- Ceph vs Sync.com
- Ceph vs Google Vertex AI
- Ceph vs AWS SageMaker
- Ceph vs Azure Machine Learning
- Ceph vs DataRobot
- Ceph vs Milvus
- Ceph vs Pinecone
- Ceph vs H2O.ai
- Ceph vs Dask
- Ceph vs Apache Spark MLlib
- Ceph vs Weaviate
- Ceph vs TensorFlow
- Ceph vs LangChain
- Ceph vs Dataiku
- Ceph vs KNIME
- Ceph vs Palantir Foundry
- Ceph vs Python
- Ray vs MinIO
- Ray vs Panzura
- Ray vs Scality RING
- Ray vs VAST Data
- Ray vs Backblaze
- Ray vs Duplicati
- Ray vs Storj
- Ray vs Tigris
- Ray vs Cloudflare R2
- Ray vs Cloudian
- Ray vs IDrive e2
- Ray vs TrueNAS
- Ray vs LucidLink
- Ray vs pCloud
- Ray vs Sync.com
- Ray vs Google Vertex AI
- Ray vs AWS SageMaker
- Ray vs Azure Machine Learning
- Ray vs DataRobot
- Ray vs Milvus
- Ray vs Pinecone
- Ray vs H2O.ai
- Ray vs Dask
- Ray vs Apache Spark MLlib
- Ray vs Weaviate
- Ray vs TensorFlow
- Ray vs LangChain
- Ray vs Dataiku
- Ray vs KNIME
- Ray vs Palantir Foundry
- Ray vs Python