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Machine Learning · head to head

DVC vs Plane

DVC logo

DVC

Machine Learning

Git-style versioning for data sets and models, with the files kept in object storage

From
Free
Rated
-
Full reviewWebsite
Plane logo

Plane

Technology

Open-source project management tool

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Plane self-hosted Community edition requires managing your own Docker/Kubernetes infra plus your own PostgreSQL, Redis, and S3-compatible/GCS/MinIO storage; no single-binary install
  • They diverge on capability: DVC covers Pointer-file versioning, Plane covers Issue tracking.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DVC and Plane actually diverge.

Attributes where DVC and Plane differ
AttributeDVCPlane
Pricing modelopen-sourcefreemium
PlatformsLinux, Mac, WindowsWeb, iOS, Android, macOS, Windows
CategoryMachine LearningTechnology
Founded20182022

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 DVC

  • Pointer-file versioning
  • Remote storage backends
  • Pipeline definitions
  • Stage caching
  • Experiment tracking
  • Metrics and plots comparison
  • Data registry pattern
  • Content-addressed cache

Only in Plane

  • Issue tracking
  • Cycles (Sprints)
  • Modules
  • Views & layouts
  • Pages (Docs)
  • Analytics
  • API access
  • Webhooks

What people use each for

The jobs each tool is most often brought in to do.

DVC

  • Making a model reproducible by tying the exact data set version, code commit and parameters together in one Git historynot Plane
  • Keeping large training data out of Git while still having a repository that describes it preciselynot Plane
  • Skipping expensive preprocessing stages that have not changed, when iterating on a later stage of a pipelinenot Plane
  • Teams that need reproducibility but cannot get approval or budget to stand up a platform for itnot Plane

Plane

  • Project and task management with cycles, modules, epics, and initiativesnot DVC
  • Documentation and knowledge management via workspace wiki tied to project worknot DVC
  • Sprint planning and issue triagenot DVC
  • Cross-functional collaboration with analytics and dashboardsnot DVC
  • Migration target from Jira, Linear, Monday, ClickUp, or Asananot DVC

Where each one falls short

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

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.

Plane

  • Self-hosted Community edition requires managing your own Docker/Kubernetes infra plus your own PostgreSQL, Redis, and S3-compatible/GCS/MinIO storage; no single-binary install
  • Cloud Free tier caps at 12 users and 500 AI credits per seat per month
  • Substantial feature gating by tier: custom work item types, workspace wiki, time tracking, dashboards, initiatives, teamspaces, and integrations require Pro or above; LDAP, granular access control, and multi-workflow approvals require Enterprise Grid
  • Guest-to-paid-member ratio capped at 1:5 on the Pro plan

Pricing, plan by plan

DVC

Free
  • Open SourceFree
    • Data versioning
    • Pipeline management
    • Experiment tracking
  • DVC StudioFree
    • Web UI
    • Team collaboration
    • Visualizations

Plane

Free
  • FreeFree
    • 500 AI credits per seat
    • Max 12 users
    • Unlimited projects
  • Pro$6/seat per month
    • 1,000 AI credits per seat
    • Unlimited users
    • Custom work item types
  • Business$13/seat per month
    • 2,000 AI credits per seat
    • Unlimited users
    • Project templates, recurring work items
  • Enterprise Grid$null/mo
    • Flexible AI credit allocation
    • Private deployments
    • Granular access control

Which should you pick?

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.
DVC review

Choose Plane if

  • You need issue tracking.
  • You want to start without paying.
  • You work on Web, iOS, Android, macOS, Windows.
  • You also want cycles (sprints).
Plane review

Questions people ask

Is DVC or Plane better?
Neither clearly leads. DVC starts at Free and Plane at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DVC or Plane?
DVC starts at Free and Plane at Free.
Does DVC or Plane run on more platforms?
DVC runs on Linux, Mac, Windows. Plane runs on Web, iOS, Android, macOS, Windows.
Can I use DVC for free?
Both have a free tier, so you can try either at no cost before committing.
What is DVC best used for?
DVC is most often used for making a model reproducible by tying the exact data set version, code commit and parameters together in one git history, keeping large training data out of git while still having a repository that describes it precisely, skipping expensive preprocessing stages that have not changed, when iterating on a later stage of a pipeline, teams that need reproducibility but cannot get approval or budget to stand up a platform for it. Of those, making a model reproducible by tying the exact data set version, code commit and parameters together in one git history and keeping large training data out of git while still having a repository that describes it precisely are not what Plane is typically brought in for.
What can DVC do that Plane cannot?
DVC covers Pointer-file versioning, Remote storage backends, Pipeline definitions, Stage caching. Plane covers Issue tracking, Cycles (Sprints), Modules, Views & layouts.

Answered from the vendors’ own pages

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.

Plane: Does Plane offer a free plan?

Yes, Plane's free tier includes 500 AI credits per seat, support for up to 12 users, and access to projects, work items, cycles, modules, layouts, views, estimates, and pages.

Source
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.

Plane: How much does Plane Pro cost?

Plane Pro costs $6/seat per month and saves 25% when billed annually. It includes 1,000 AI credits per seat, unlimited users, and access to custom work item types, wiki, time tracking, and integrations.

Source
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.

Plane: What is the difference between Plane's paid tiers?

Pro ($6/seat/month) includes 1,000 AI credits and workspace wiki. Business ($13/seat/month) adds 2,000 AI credits, project templates, and recurring work items. Enterprise Grid offers custom pricing with multiple workflows and LDAP support.

Source
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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