Head-to-Head Comparison
lakeFS vs DVC (Data Version Control)
Compare features, pricing, integrations, and community reviews
lakeFS
AI ToolslakeFS provides Git-like version control and management for data lakes built on object storage. It enables isolated experimentation, data governance, and atomic operations, including zero-copy branching on petabytes of data. This platform offers a higher-level abstraction for managing data lifecycle and collaboration within data lakes. It supports reproducible ML workflows and is designed for petabyte-scale data. lakeFS provides a data lake versioning platform with an API, offering capabilities for data management and ML/AI use cases. Both open source and enterprise versions are available.
DVC (Data Version Control)
AI ToolsDVC provides Git-like data version control for AI/ML and data science teams, applying software engineering best practices to data management. It focuses on versioning data and machine learning models, integrating seamlessly with Git for both code and data management. The tool offers a command-line interface for managing data and machine learning processes. It integrates data versioning, experiment tracking, and pipeline management, building on top of object storage to support reproducible machine learning workflows.
Pricing
Community Verdict
lakeFS
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DVC (Data Version Control)
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At a Glance
lakeFS
Best For
agents, code
Pricing
freemium
Key Features
Provides Git-like version control for data lakes on object storage, supporting petabyte-scale data. · Released version 1.0 in October 2023, including integrations with Databricks and Apache Iceberg. · Acquired DVC (Data Version Control) in November 2025, aiming to unite data version control pioneers.
DVC (Data Version Control)
Pricing
free
Key Features
An open-source version control system specifically engineered for machine learning (ML) projects. · Integrates seamlessly with Git for both code and data management. · Supports object storage including S3, Google Cloud Storage, Azure, SSH, and HDFS.
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