Suggestions appear as you type. Use the up and down arrows to choose one and Enter to open it.

This page's audience our own tag's counts — open to see them
–Visits
–Page views
–Clicks to vendors
–Time on page
–Reading now
Clicks to vendors, by tool
  • –
Top countries
  • –
Devices
  • –

– · visits, page views and clicks counted by our own tag, which counts more than our checked analytics; every figure rounded down · how we count

lakeFS review

Freemium#6 of 19 in Data Lake SoftwareData Version Control Tools

A governed, Git-like control layer for versioned data lakes.

8.5/10Editor score
lakeFS8.5 Visit lakeFS

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

lakeFS is an open-source and commercial data version-control platform for data, AI, and ML teams. It adds Git-like branching, commits, merges, rollbacks, tags, hooks, audit trails, lineage, and zero-copy data environments over object storage. Teams can work with structured and unstructured data, including Iceberg and Delta Lake, while keeping data in existing storage systems. It fits organizations that need governed development, testing, sharing, and reproducibility across data lakes rather than a standalone system for every ingestion and query task.

The Open Source plan is free forever and includes format-agnostic data version control, zero-copy branching, atomic merges, configurable garbage collection, and Data CI/CD hooks. Enterprise pricing is handled through sales and adds a choice of managed lakeFS Cloud or self-managed deployment, along with RBAC, SSO and SCIM, Metadata Search, the Iceberg REST Catalog, and enterprise support. A 15-day trial applies to lakeFS Enterprise, while the Community edition remains the permanent free option. This structure gives smaller teams a clear way to start and larger organizations a path to additional governance and support capabilities.

Integration breadth is a significant fit consideration. lakeFS connects with Apache Spark, Trino, Presto, DuckDB, Databricks, AWS Glue, Amazon Athena, Starburst Galaxy, Dremio, Delta Lake, Apache Kafka, Glue Data Catalog, Unity Catalog, MLflow, and Hugging Face Datasets. It also offers an S3-compatible gateway, native SDKs, and support for multiple cloud and on-premises object-storage backends. Choose lakeFS when versioned environments, quality workflows, lineage, governed sharing, and rollback matter most. Consider a broader data lake product when ingestion and querying are the primary requirements.

lakeFS pros and cons

  • Where it wins
    • Git-like branching, merges, tags, and rollbacks for data
    • Free-forever open-source edition with zero-copy branching
    • Broad integrations across analytics, catalogs, ML, and storage
  • Where it doesn't
    • More specialized in versioning than ingestion and querying
    • Enterprise pricing requires contacting sales
    • Enterprise trial is separate from the permanent Community edition

lakeFS fact sheet, pricing and score →

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.

Last updated · How we research and update