DVC
TreeverseDVC (Data Version Control) versions datasets and models by keeping their contents in external storage and their version metadata in Git, so a repository records which data produced which result. It also defines pipelines as a dependency graph and tracks experiment runs and metrics against them. A command-line tool and a VS Code extension are the two interfaces.
Openness
5 high confidence- license
- Apache-2.0(OSI)
- source
- public
- core features withheld
- no
Apache-2.0 license body confirmed. The repository is public and unarchived and builds the whole product, and the README describes no paid tier, enterprise edition or license-gated build beside it, so source is public and the core ungated.
- https://raw.githubusercontent.com/treeverse/dvc/main/LICENSE recorded 2026-09-30
LICENSE file is the Apache-2.0 text: "Apache License" and "Version 2.0, January 2004" and "TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION".
- https://raw.githubusercontent.com/treeverse/dvc/main/README.rst recorded 2026-09-30
README says DVC will "Store them in your cloud storage but keep their version info in your Git repo"; searched the body for enterprise, paid tier and license key: none.
Adoption
4 high confidencePyPI downloads of dvc drive this reading, since that package is the channel DVC declares for distribution. The figure therefore measures use of the tool itself, not a proxy for it.
- https://pypistats.org/api/packages/dvc/recent recorded 2026-08-18
last_month downloads = 2,664,290 for dvc
Capability
3 medium confidenceDVC versions datasets and models against Git and orchestrates pipelines and experiment tracking across many storage backends, but it stores nothing and serves no queries itself. That keeps it two steps below Vespa, a complete distributed retrieval system.
- https://raw.githubusercontent.com/treeverse/dvc/main/README.rst recorded 2026-09-30
README describes "Store and share data artifacts (like Git-LFS but without a server)" connected with a Git repository, plus pipelines and experiment tracking.
- https://raw.githubusercontent.com/treeverse/dvc/main/README.rst recorded 2026-09-30
README describes DVC pipelines as "computational graphs" that "connect code and data together", with experiment versioning to compare results by metrics.
- https://raw.githubusercontent.com/treeverse/dvc/main/README.rst recorded 2026-09-30
README says DVC supports "multiple remote storage platforms - any cloud (S3, Azure, Google Cloud, etc.) or on-premise network storage (via SSH, for example)".
Verified 2026-09-24