DVC

Model Store Overview

Vendor Name	DVC
Stand-alone vs. Platform	Stand-alone
Delivery Model	Open-source
Clouds Supported	Open-source
Pricing Model	Open-source
Service Level Guarantees	None
Support	Open-source: community (Discord server, GH issues, self-hosted forum, support email, social media)
SSO, ACL	N/A
Security and Compliance	None

Setup	Familiarity with Git workflows and CLI.
Flexibility, Speed, and Accessibility	Supports many cloud storage providers: S3, Azure, Google Cloud, Google Drive, Aliyun, SSH, HDFS, HTTP, WebDav (https://dvc.org/doc/command-reference/remote/modify#available-parameters-per-storage-type)
Model Versioning, Lineage, and Packaging	Uses Git to track metadata/hashes of data&models. Uses YAML to store reproducible pipelines (data download sources, commands with data inputs & outputs).
Log and Display of Metadata	Supports parameters, metrics, plots, source control, and large artifacts like data and models across multiple commits & experiments. Checkpoints for live per-epoch logging.
Comparing Experiments and Models	Tables & plots (see above) for parameters & metrics, including overlaid learning curves
Organizing and Searching Experiments and Models	Use Git-based experiments workflow to view and filter/sort by parameters, metrics, and commits. Save results in standard Git workflow (branches, tags, commit messages, git-blame, git-grep, etc).
Model Review, Collaboration, and Sharing	N/A (user-provided cloud storage credentials can have limited permissions)
CI/CD/CT Compatibility	Cloud storage provider credentials may be provided as secret env vars in CI/CD
Integrations	Specifically designed to be language and user-workflow agnostic. Supports and integrates with anything.

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