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DVC
Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.

About DVC
DVC is a version control system for data science and machine learning projects. It uses a Git-like model to manage data, models, and experiments, applying software engineering practices to data, AI/ML, and data science work. The homepage describes DVC as a Git extension for small data science projects, with minimal workflow overhead.
The homepage also presents lakeFS as a separate offering for enterprise AI and data engineering teams, with data version control infrastructure for petabyte-scale object stores and data lakes. A blog post on the site describes an end-to-end lineage workflow that combines DVC with Amazon SageMaker AI and MLflow. The post covers dataset-level and record-level lineage. Pricing is not stated on the homepage.
Key features
- Git-like model for versioning data, models, and experiments
- Data version control for data science workflows with minimal overhead
- Visual Studio Code extension listed on the homepage
- Data version control infrastructure for petabyte-scale object stores and data lakes (lakeFS)
- Blog example of dataset-level and record-level lineage with Amazon SageMaker AI and MLflow
- Experiment tracking and lineage workflow described with Amazon SageMaker AI MLflow Apps
- Applies Git-like version control concepts to data, models, and experiments
- Described on the homepage as having minimal overhead for data science workflows
- Homepage links a Visual Studio Code extension for DVC
- The homepage positions DVC for small data science projects, while large-scale enterprise environments are described under lakeFS
DVC at a glance
- Website
- dvc.org
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
DVC alternatives
Tools and sites you could use instead, ranked by how closely they match.
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Polyaxon describes its repository as infrastructure for AI orchestration and control.
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
TPOT uses genetic programming to optimize machine learning pipelines in Python.
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DVC FAQ
Does DVC support large enterprise data lakes?
Is there a VS Code extension for DVC?
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