oneDAL is a C++ and DPC++ library for accelerated machine learning routines on tabular data, governed by the UXL Foundation.
DVC
DVC tracks data versions and machine learning experiments for collaborative development.

About DVC
DVC is a command line tool with a VS Code extension for versioning data, models, and machine learning experiments alongside Git code. It keeps version metadata in the Git repository while storing data and model files in a cache outside Git.
It defines pipelines that connect code, data inputs, commands, and outputs and reruns only steps affected by changes. Experiments are tracked locally for comparison and reproduction, with code shared through Git hosting and data pushed to cloud or network remotes. The VS Code extension covers experiment tracking and data management and requires a separate install of core DVC.
Key features
- Version data and models with metadata stored in Git repo
- Store data cache outside Git and push to S3, Azure, Google Cloud, SSH
- Define pipelines linking code, data inputs, commands, and outputs
- Rerun only pipeline steps affected by changes
- Track, compare, and apply experiments locally using Git
- Compare parameters, metrics, models, and performance plots
- Open source tool with command line interface and VS Code extension
- Works with existing Git hosting and multiple cloud or SSH remotes
- Tracks experiments in local Git repo without requiring separate servers
- VS Code extension covers experiment tracking and data management, with pipeline support still pending
- VS Code extension requires separate installation of core DVC
DVC at a glance
- Website
- github.com/iterative/dvc
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- 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.
Cleanlab provides a Python library for data quality and machine learning with messy real world data and labels.
Lance provides an open lakehouse format for multimodal AI, with vector indexing and data versioning.
DVCLive logs and tracks machine learning metrics, parameters, and models with Git or DVC.
19 Questions assigns attributes to objects using machine learning and Bayesian inference, according to its project description.
Feature Engine provides Python tools for feature engineering and selection that are compatible with scikit-learn.
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DVC FAQ
How does DVC store data in relation to Git?
Where can shared data be stored?
Does the VS Code extension work without installing DVC separately?
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