Softwr

Software · head to head

DVC vs JMP

DVC logo

DVC

Software

Data version control for machine learning projects

From
Free
Rated
-
JMP logo

JMP

Software

Statistical discovery software from SAS

From
Free
Rated
-

The short version

  • Each has a real cost: DVC dVC is Apache 2.0 licensed open source with no enterprise tier or paid support offering documented in the project itself; teams needing SLA-backed support get nothing from the DVC project directly.; JMP the Internet Archive's capture of JMP's homepage on 13 January 2020 named five distinct editions, JMP, JMP Live, JMP Pro, JMP Clinical, and JMP Genomics, each targeting a different analysis use case, with no price figure published for any.
  • They diverge on capability: DVC covers Data versioning, JMP covers Interactive statistics.

Where they differ

Only the attributes on which DVC and JMP actually diverge.

Attributes where DVC and JMP differ
AttributeDVCJMP
Pricing modelopen-sourcesubscription
PlatformsLinux, Mac, WindowsMac, Windows
Founded20181976

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).

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

  • Data versioning
  • Pipeline management
  • Experiment tracking
  • Remote storage
  • Git integration
  • Git
  • S3
  • Azure Blob

Only in JMP

  • Interactive statistics
  • Dynamic visualization
  • Design of experiments
  • Predictive modeling
  • Quality control
  • SAS
  • Python
  • R

Both cover

  • Mac support
  • Windows support

What people use each for

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

DVC

  • Machine learning
  • Data analysis
  • Model training
  • Predictive analytics

JMP

  • Machine learning
  • Data analysis
  • Model training
  • Predictive analytics

Both are used for machine learning, data analysis, model training, predictive analytics, on those jobs the choice comes down to price and fit rather than capability.

Where each one falls short

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

DVC

  • DVC is Apache 2.0 licensed open source with no enterprise tier or paid support offering documented in the project itself; teams needing SLA-backed support get nothing from the DVC project directly.

JMP

  • The Internet Archive's capture of JMP's homepage on 13 January 2020 named five distinct editions, JMP, JMP Live, JMP Pro, JMP Clinical, and JMP Genomics, each targeting a different analysis use case, with no price figure published for any.

Pricing, plan by plan

DVC

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

JMP

Free
  • TrialFree
    • 30-day trial
    • Full features
  • JMP$1785/year
    • Core JMP
    • Standard features

Which should you pick?

Choose DVC if

  • You need data versioning.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want pipeline management.

Choose JMP if

  • You need interactive statistics.
  • You want to start without paying.
  • You work on Mac, Windows.
  • You also want dynamic visualization.

Questions people ask

Is DVC or JMP better?
Neither clearly leads. DVC starts at Free and JMP at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DVC or JMP?
DVC starts at Free and JMP at Free.
Does DVC or JMP run on more platforms?
DVC runs on Linux, Mac, Windows. JMP runs on Mac, 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 machine learning, data analysis, model training, predictive analytics.
What can DVC do that JMP cannot?
DVC covers Data versioning, Pipeline management, Experiment tracking, Remote storage. JMP covers Interactive statistics, Dynamic visualization, Design of experiments, Predictive modeling. Both handle Mac support, Windows support.

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