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lakeFS
What it is
lakeFS provides version control and governance for petabyte-scale multimodal data, recording changes to support auditability. Its engine uses Git-like branches, commits, merges, and rollbacks to manage data versions. Branches create isolated environments without copying data or adding storage costs. Write-Audit-Publish workflows use automated hooks and human review to check changes before merging. Immutable commits, tags, and lineage connect experiments and agent actions to the data versions behind them. Listed governance controls include role-based access, geo-based policies, data immutability, SSO, and SCIM; lakeFS states that it is SOC 2 compliant and provides audit trails and lineage. It supports AWS S3, Azure Blob, Google Cloud Storage, and on-premises object stores such as MinIO. Integrations include Spark, Trino, DuckDB, Databricks, MLflow, SageMaker, Vertex AI, Kubeflow, Airflow, and Airbyte. Enterprise can run as managed lakeFS Cloud or as a self-managed deployment on-premises, in a private cloud, or in an air-gapped environment. Pricing is on request. A 15-day trial provides full Enterprise access and enterprise support from lakeFS experts.
For and against
For
- Git-like versioning includes branches and rollbacks
- Zero-copy branches avoid added storage costs
- Supports automated checks and human review
- Works with major cloud and on-premises object stores
- Offers managed and self-managed deployment options
Against
- Enterprise pricing is available only on request
- Trial lasts 15 days
- Enterprise deployment choices may require self-management
The verdict
lakeFS combines data version control with governance and audit trails for large-scale data workflows. Teams should review the deployment options and request pricing to assess the Enterprise fit.
Who it suits
lakeFS is aimed at data engineers, data scientists, ML engineers, ML platform teams, and agentic AI initiatives. It may suit teams that need data versioning, auditability, and governed access across supported storage environments.
Plans and prices
lakeFS Enterprise
Managed lakeFS Cloud or self-managed deployment on-premises, in your own cloud, or air-gapped
Read 29 Sep 2026 · lakefs.io
On the record
- Access controls
- The product page lists role-based access control, geo-based policies, data immutability, SSO, and SCIM.lakefs.io · read 29 Sep 2026
- Cloud connectivity
- The pricing page says lakeFS Cloud supports AWS, Azure, and GCP, and that a private link can connect a customer's VPC to lakeFS Cloud.lakefs.io · read 29 Sep 2026
- Compliance
- The product page states that lakeFS is SOC 2 compliant and provides audit trails and lineage.lakefs.io · read 29 Sep 2026
- Data quality
- Write-Audit-Publish workflows use automated hooks and human review to check changes before they merge.lakefs.io · read 29 Sep 2026
- Deployment
- lakeFS Enterprise can run as a managed Cloud service or be self-managed on S3-compatible infrastructure; the pricing page also lists on-premises, private cloud, and air-gapped deployment.lakefs.io · read 29 Sep 2026
- Integrations
- The integrations documentation lists tools including Spark, Trino, DuckDB, Databricks, MLflow, SageMaker, Vertex AI, Kubeflow, Airflow, and Airbyte.docs.lakefs.io · read 29 Sep 2026
- Intended users
- The product page describes use by data engineers, data scientists, ML engineers, ML platform teams, and agentic AI initiatives.lakefs.io · read 29 Sep 2026
- Purpose
- lakeFS provides governed access to petabyte-scale multimodal data and records data changes for auditability.lakefs.io · read 29 Sep 2026
- Reproducibility
- Immutable commits, tags, and lineage tie experiments and agent actions to the data versions that produced them.lakefs.io · read 29 Sep 2026
- Storage
- lakeFS supports AWS S3, Azure Blob, Google Cloud Storage, and on-premises object stores such as MinIO.lakefs.io · read 29 Sep 2026
- Trial and support
- The 15-day trial offers full lakeFS Enterprise access and enterprise support from lakeFS experts.lakefs.io · read 29 Sep 2026
- Version control
- Its data version control engine uses Git-like branches, commits, merges, and rollbacks.lakefs.io · read 29 Sep 2026
- Zero-copy branches
- Branches create isolated data environments without copying data or adding storage costs.lakefs.io · read 29 Sep 2026
