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Software · head to head

Anaconda vs DVC

Anaconda logo

Anaconda

Software

The world's most popular data science platform

From
Free
Rated
-
Full reviewWebsite
DVC logo

DVC

Software

Data version control for machine learning projects

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Anaconda dependency resolution slower than pip due to SAT solver complexity; 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.
  • They diverge on capability: Anaconda covers Conda package manager, DVC covers Data versioning.

Where they differ

Only the attributes on which Anaconda and DVC actually diverge.

Attributes where Anaconda and DVC differ
AttributeAnacondaDVC
Pricing modelUnknownopen-source
PlatformsWindows, macOS, Linux, Web/CloudLinux, Mac, Windows
Founded20122018

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 Anaconda

  • Conda package manager
  • Environment management
  • 1500+ packages
  • Navigator GUI
  • Cross-platform support
  • Jupyter
  • VS Code
  • PyCharm

Only in DVC

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

Both cover

  • Linux support
  • Mac support
  • Windows support

What people use each for

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

Anaconda

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

DVC

  • 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.

Anaconda

  • Dependency resolution slower than pip due to SAT solver complexity
  • Not all PyPI packages available through default Anaconda repository
  • Requires paid licenses for organizations with 200+ employees
  • Larger disk footprint than minimal Python installations

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.

Pricing, plan by plan

Anaconda

Free
  • FreeFree
    • 600+ pre-installed packages
    • Anaconda Navigator
    • 5GB cloud storage
  • Starter$15/month
    • 10GB cloud storage per user
    • Professional development environment
    • Team workspace controls
  • Business$50/month
    • Automated vulnerability scanning
    • Audit trails
    • Enterprise SSO

DVC

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

Which should you pick?

Choose Anaconda if

  • You need conda package manager.
  • You want to start without paying.
  • You work on Windows, macOS, Linux, Web/Cloud.
  • You also want environment management.
Anaconda review

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

Questions people ask

Is Anaconda or DVC better?
Neither clearly leads. Anaconda 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, Anaconda or DVC?
Anaconda starts at Free and DVC at Free.
Does Anaconda or DVC run on more platforms?
Anaconda runs on Windows, macOS, Linux, Web/Cloud. DVC runs on Linux, Mac, Windows.
Can I use Anaconda for free?
Both have a free tier, so you can try either at no cost before committing.
What is Anaconda best used for?
Anaconda is most often used for machine learning, data analysis, model training, predictive analytics.
What can Anaconda do that DVC cannot?
Anaconda covers Conda package manager, Environment management, 1500+ packages, Navigator GUI. DVC covers Data versioning, Pipeline management, Experiment tracking, Remote storage. Both handle Linux support, Mac support, Windows support.

Answered from the vendors’ own pages

Anaconda: Does Anaconda have a free version?

Yes. Anaconda Distribution is free and includes 600+ pre-installed data science packages, Navigator, and 5GB of cloud storage. Organizations with 200+ employees must use paid plans unless they qualify for academic or non-profit exemptions.

Source
Anaconda: What is the difference between Anaconda Distribution and Miniconda?

Anaconda Distribution includes 600+ pre-installed packages optimized for data science out of the box. Miniconda is lightweight with only conda, Python, and essential packages, requiring manual installation of additional libraries.

Source
Anaconda: Does Anaconda integrate with VS Code?

Yes. Anaconda environments can be activated in VS Code, and you can run Jupyter Notebooks directly. Both JupyterLab and conda can be managed through the VS Code Jupyter extension.

Source
Anaconda: What platforms does Anaconda support?

Anaconda runs on Windows, macOS, and Linux, with cloud-based deployment options. Anaconda Notebooks provides a cloud-based JupyterLab environment requiring no local installation.

Source
Anaconda: Do all PyPI packages work with Anaconda?

Not all PyPI packages are available through Anaconda's default conda repository. When a package is unavailable in conda, you can install it from conda-forge or pip as an alternative.

Source
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