What is Dvc used for?

DVC is an open-source version control system for data science and machine learning projects that applies software engineering best practices to data management. It is a good fit for data versioning for small data science projects, and organizing data and models in machine learning workflows.

Yes. Dvc is open source under the Apache-2.0 licence. Its source code is on GitHub at treeverse/dvc and is written mainly in Python.

Yes. Dvc is open source, so the software itself is free to use.

Yes. Dvc can be self-hosted on your own server or infrastructure.

What is Dvc an alternative to?

Dvc is an open-source alternative to Arize AI, Weights & Biases, Dataiku and Comet. Other open-source alternatives to Arize AI include Kubeflow, MLflow and Pachyderm.

Is Dvc actively maintained?

Yes. The most recent commit to Dvc was on 12 October 2026, and the latest release is 3.67.1, published on 31 March 2026. The project has 16k stars on GitHub.

Dvc: open-source alternative to Arize AI, Weights & Biases

About Dvc

DVC is a free and open-source version control system designed for data science and machine learning projects. It uses a Git-like model to manage data, models, and experiments, bringing software engineering best practices to data teams.

The tool is intended for individual data scientists working on small projects, offering a Git extension that integrates with existing workflows. It also provides a VS Code extension for easier use.

Key features

Data version control using a Git-like model
Management of data, models, and experiments
Integration with Git for local workflows
VS Code extension available

Good fit for

Data versioning for small data science projects
Organizing data and models in machine learning workflows

Built with: Python tools
Tags: data version control; machine learning; data science; git extension; open source

Dvc: questions and answers

What is Dvc used for?: DVC is an open-source version control system for data science and machine learning projects that applies software engineering best practices to data management. It is a good fit for data versioning for small data science projects, and organizing data and models in machine learning workflows.
Is Dvc open source?: Yes. Dvc is open source under the Apache-2.0 licence. Its source code is on GitHub at treeverse/dvc and is written mainly in Python.
Is Dvc free?: Yes. Dvc is open source, so the software itself is free to use.
Can I self-host Dvc?: Yes. Dvc can be self-hosted on your own server or infrastructure.
What is Dvc an alternative to?: Dvc is an open-source alternative to Arize AI, Weights & Biases, Dataiku and Comet. Other open-source alternatives to Arize AI include Kubeflow, MLflow and Pachyderm.
Is Dvc actively maintained?: Yes. The most recent commit to Dvc was on 12 October 2026, and the latest release is 3.67.1, published on 31 March 2026. The project has 16k stars on GitHub.