Ross ROSS = Recommend OSS · open-source software intelligence for agents

treeverse/lakeFS

lakeFS - Data version control for your data lake | Git for data observed · 2026-08-28

github.com/treeverse/lakeFS · homepage · Go · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

94/100

  • Activity 98
  • Release rhythm 84
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 8
  • age_days: 2547
  • days_rel: 28
  • days_push: 14
  • n_releases_24m: 68

Full methodology

Adoption not part of the score

5496 stars · 474 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

lakeFS is an open-source data version control service that turns object storage (S3, Azure Blob, GCS) into a Git-like repository with branching, committing, merging, and rollback over data lakes. It is S3-API compatible, works with Spark, Athena, DuckDB, Presto, and pandas, and provides zero-copy isolated branches for ETL testing and AI agent workflows.

Use cases

  • version control for data lake on S3
  • test ETL jobs in isolated dev branch before merging to production
  • roll back bad data loads atomically
  • give AI agents isolated zero-copy branches of production data
  • reproducible snapshots of training data
  • manage data quality checks with hooks before merging
  • query data lake with Spark or DuckDB against versioned branches

When to choose

  • you run a data lake on S3, Azure Blob, or GCS and need Git-like branching, merging, and rollback over data
  • you need isolated dev/test environments for ETL without copying data
  • you want reproducible, auditable data versions for analytics, ML training, or AI agents
  • you want an S3-compatible API so existing data tools work unchanged

When to avoid

  • your data lives in a traditional database rather than object storage
  • you only need simple file backups or sync rather than versioned data operations
  • you need row-level versioning inside a single table rather than object-level lake versioning
  • you cannot operate an additional self-hosted service or prefer a fully managed warehouse

Facets

service · maturity stable

version-control database etl object-storage api-gateway workflow-automation big-data databases analytics data-science self-hosted artificial-intelligence go self-hosted cloud cross-platform data-lake data-version-control git-for-data s3-compatible zero-copy-branching object-storage apache-spark data-quality ai-agents data-engineering docker web-server

10 sources

Member repositories

RepositoryRoleHealth v2
treeverse/lakeFSmain94

For agents

markdown · JSON · MCP: product_card(name="treeverse/lakeFS")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem