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Machine Learning & Data Science · head to head

DVC vs Weka

DVC logo

DVC

Machine Learning & Data Science

Data version control for machine learning projects

From
Free
Rated
-
Full reviewWebsite
Weka logo

Weka

Machine Learning & Data Science

Collection of machine learning algorithms

From
Free
Rated
-
Full reviewWebsite

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.; Weka the package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
  • They diverge on capability: DVC covers Data versioning, Weka covers Classification.

Where they differ

Only the attributes on which DVC and Weka actually diverge.

Attributes where DVC and Weka differ
AttributeDVCWeka
Founded20181993

Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), platforms (Linux, Mac, Windows), user rating (Not yet rated), category (Machine Learning & Data Science).

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 Weka

  • Classification
  • Regression
  • Clustering
  • Association rules
  • Feature selection
  • Java
  • R
  • Python

Both cover

  • Linux support
  • Mac support
  • Windows support

What people use each for

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

DVC

  • Machine learningnot Weka
  • Data analysisnot Weka
  • Model trainingnot Weka
  • Predictive analyticsnot Weka

Weka

  • Teaching and exploring classic machine learning algorithms through a GUInot DVC
  • Running data mining experiments and preprocessing without writing codenot DVC

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.

Weka

  • The package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
  • Weka is split into a stable 3.8 branch that receives only bug fixes and compatibility-safe upgrades and a 3.9 development branch that may receive features that break compatibility
  • Weka requires a 64-bit Java VM; the bundled installers ship Bellsoft OpenJDK 25 per platform and architecture

Pricing, plan by plan

DVC

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

Weka

Free
  • Open SourceFree
    • All ML algorithms
    • GUI and CLI
    • Java API

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.
DVC review

Choose Weka if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want regression.
Weka review

Questions people ask

Is DVC or Weka better?
Neither clearly leads. DVC starts at Free and Weka at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DVC or Weka?
DVC starts at Free and Weka at Free.
Does DVC or Weka run on more platforms?
Both run on Linux, Mac, Windows, so platform support will not decide this one for you.
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. Of those, machine learning and data analysis are not what Weka is typically brought in for.
What can DVC do that Weka cannot?
DVC covers Data versioning, Pipeline management, Experiment tracking, Remote storage. Weka covers Classification, Regression, Clustering, Association rules. Both handle Linux support, Mac support, Windows support.
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