Dataloop vs DVC (Data Version Control)

Side-by-side comparison of Dataloop and DVC (Data Version Control): pricing, features, API access, and community ratings.

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	Dataloop The AI-ready Data Stack for unstructured data, multimodal pipelines, and the full AI data lifecycle Visit	DVC (Data Version Control) Manage data the way code is managed — Git-like version control for AI/ML and data science. Visit
Category	Chat assistants	Chat assistants
Pricing	Enterprise	Freemium
Starting price
Free tier
Audience	All audiences	Technical
API available
Open source
Self-hostable
Model provider
Founded	2017	2017
Headquarters	Tel Aviv	San Francisco, USA
Key strengths	·End-to-end AI data lifecycle management for unstructured data ·Visual drag-and-drop pipeline builder with Python SDK support ·Built-in human-in-the-loop / RLHF feedback integration ·Marketplace of 100s of pre-built models, pipelines, and nodes	·Git-like versioning for datasets and ML models ·Open source with a large, active community ·Seamlessly integrates with existing Git workflows ·Supports petabyte-scale data lakes and object stores via lakeFS