File Storage · head to head
Ceph vs DVC
Ceph
File Storage
Open source distributed storage providing object, block and file from one cluster
- From
- Free
- Rated
- -
DVC
Machine Learning
Git-style versioning for data sets and models, with the files kept in object storage
- 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.; DVC dVC knows only about files that were added through DVC, so one person copying data in by hand leaves a pipeline that reproduces to a different answer with no error and nothing to indicate which result is the real one.
- They diverge on capability: Ceph covers RADOS object store, DVC covers Pointer-file versioning.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Ceph and DVC 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 DVC
- Pointer-file versioning
- Remote storage backends
- Pipeline definitions
- Stage caching
- Experiment tracking
- Metrics and plots comparison
- Data registry pattern
- Content-addressed cache
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 DVC
- Growing past the point where a proprietary array upgrade costs more than a rack of commodity serversnot DVC
- Research and media environments with petabytes of data and staff who can operate storagenot DVC
- Providing an S3 endpoint on premises with multi site replication under your own controlnot DVC
DVC
- Making a model reproducible by tying the exact data set version, code commit and parameters together in one Git historynot Ceph
- Keeping large training data out of Git while still having a repository that describes it preciselynot Ceph
- Skipping expensive preprocessing stages that have not changed, when iterating on a later stage of a pipelinenot Ceph
- Teams that need reproducibility but cannot get approval or budget to stand up a platform for itnot 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.
DVC
- DVC knows only about files that were added through DVC, so one person copying data in by hand leaves a pipeline that reproduces to a different answer with no error and nothing to indicate which result is the real one.
- Every tracked revision writes a new pointer into Git and a new copy into the remote cache, so a data set revised daily accumulates full copies in object storage and the storage bill grows with the length of the history rather than the size of the data.
- Merge conflicts in dvc.lock and dvc.yaml are routine on parallel branches and are unreadable to anyone who has not learned the format, which in practice means the person who introduced DVC resolves all of them.
- Checking out a large data set materialises it in the working directory, so a laptop working against a repository with several hundred gigabytes tracked needs disk for the workspace and the cache together, and the reflink or hardlink optimisations that avoid doubling that are filesystem-dependent.
- It has no access control of its own and inherits whatever the remote grants, so a repository everyone can read plus a bucket everyone can read means everyone can reconstruct every historical version of every data set, which is frequently not what was intended.
Pricing, plan by plan
Ceph
Free- CephFree
- Full functionality, no capacity limit
- Object, block and file interfaces
- Community support via mailing list and Slack
DVC
Free- Open SourceFree
- Data versioning
- Pipeline management
- Experiment tracking
- DVC StudioFree
- Web UI
- Team collaboration
- Visualizations
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 DVC if
- You need pointer-file versioning.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want remote storage backends.
Questions people ask
- Is Ceph or DVC better?
- Neither clearly leads. Ceph starts at Free and DVC at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Ceph or DVC?
- Ceph starts at Free and DVC at Free.
- Does Ceph or DVC run on more platforms?
- Ceph runs on Linux. DVC 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 DVC is typically brought in for.
- What can Ceph do that DVC cannot?
- Ceph covers RADOS object store, RADOS Gateway, RBD block devices, CephFS. DVC covers Pointer-file versioning, Remote storage backends, Pipeline definitions, Stage caching.
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.
DVC: Does DVC put my data in Git?
No. Git gets a small pointer file containing a hash. The data goes to a cache on disk and to a remote you configure, such as an S3 bucket.
Ceph: 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.
DVC: Do I need to run a server?
No, and that is most of its appeal. It is a command line tool plus storage you already have. DVC Studio, the hosted web interface, is optional and separately paid.
Ceph: Can I buy support?
Yes. IBM sells IBM Storage Ceph and SUSE and others have offered supported builds; the upstream project itself is free.
DVC: How is it different from Git LFS?
Git LFS versions large files and stops there. DVC also defines pipelines, tracks which stage produced which output, records metrics and lets you compare experiments, and it works with ordinary object storage rather than an LFS server.
Ceph: 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.
DVC: Is it free?
The tool is Apache 2.0 and free. You pay for the object storage that holds the data, and optionally for DVC Studio.
DVC: Can several people work on the same data set?
Yes, through the shared remote, but only if all of them use DVC for every change. The tool cannot enforce a discipline it does not own, and a single manual copy silently breaks the guarantee.
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