DVC
MLOps & Infrastructure
Overview
DVC (Data Version Control) is an open-source version control system for machine learning projects that provides Git-style tracking for datasets, models, metadata, and pipeline definitions. It supports reproducible data pipelines, experiment management, and integration with cloud storage. DVC enables data science teams to version their data and models alongside code for reproducible ML workflows.
- Pricing model
- Free
- Deployment
- Self-hosted / on-premises, CLI / IDE plugin
- Regions served
- Global
- Categories
- CLI / IDE plugin, Free, MLOps & Infrastructure, Software & technology, Workflow orchestration, Self-hosted / on-premises, MLOps & model tooling, Predictive / classical ML
- Last updated
- 2 October 2026
- Published
- 2 October 2026
Use cases
Deployment options
Data sources & provenance
Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.
- Data quality
- Data quality: Editorially Reviewed
- Primary source
- dvc.org
- Sources cited
- 2
- Last reviewed
- 28 September 2026
- Last updated
- 2 October 2026
Spotted something out of date?
Anyone can suggest a correction — you don't need an account. An editor checks every suggestion against the sources before the record changes.