DVC

What is DVC?

Version control for data and ML pipelines.

Who is DVC best for?

DVC is best for data scientists and ML engineers in Git who want to version datasets, models and pipelines next to their code.

• Data scientists on smaller projects

  The maker pitches DVC as a Git extension for individual data scientists who want data version control with little setup.

• Versioning data and models

  Large files stay in your own cloud or on-premise storage while their versions are recorded in the Git repo.

• Reproducible ML pipelines

  Pipelines describe how each model is built from code and data, and only the steps a change affects run again.

• Experiment tracking without a server

  Experiments are tracked in the local Git repo and compared by parameters and metrics, from the terminal or the VS Code extension.

How much does DVC cost?

DVC is free and open source under the Apache 2.0 license, with no paid tier.

DVC and its VS Code extension are both marked free and open source. The same team sells lakeFS Enterprise, a separate product for petabyte-scale data lakes, through demos. Full pricing on dvc.org. We checked these prices on 28 Sep 2026.

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Is DVC open source?

Yes. DVC's code is public under the Apache 2.0 licence, so you can read it, change it and run it yourself.

Questions about DVC