lakeFS
lakeFS (Treeverse, Inc.) provides Git-like data version control for S3-compatible object storage-based data lakes, serving enterprise AI, ML, and data engineering teams at organizations such as Arm, Lockheed Martin, Volvo, and NASA with zero-copy branching, atomic merges, and AI-ready data governance.
- Company typePrivate
- Founded2021
- HeadquartersSanta Monica, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What lakeFS does
lakeFS (Treeverse, Inc.) develops a Git-like data version control system that operates as a control-plane layer on top of S3-compatible object storage, enabling enterprises to apply repository, branch, commit, merge, and rollback semantics to petabyte-scale data lakes. The platform is format-agnostic across Delta Lake, Apache Iceberg, and Apache Hudi, integrates with major compute engines (Spark, Trino, Databricks, Snowflake, Dremio), orchestrators (Airflow, Dagster, Prefect, Kubeflow), and ML platforms (SageMaker, Vertex AI, MLflow, Weights & Biases, Hugging Face), and provides features including zero-copy branching, atomic merge promotion, immutable commits, Write-Audit-Publish validation, and automated garbage collection with retention policies. Customers include Arm, Lockheed Martin, Volvo, Bosch, NASA, the U.S. Department of Energy (Idaho National Laboratory), Amazon, Microsoft, Netflix, and Overture Maps, spanning semiconductors, aerospace and defense, automotive, government research, and AI/ML engineering workloads.
The company operates a three-tier commercial model: a free Apache 2.0 open-source edition distributed via GitHub (5.2k+ stars) that anchors a product-led growth funnel, a managed lakeFS Cloud SaaS offering with a free trial for self-serve adoption, and a quote-based lakeFS Enterprise edition with advanced capabilities (RBAC, SSO, hooks, auditing, lakeFS Mount, transactional mirroring, managed GC) sold through field sales to large enterprises and public-sector buyers. The company has dual corporate entities — Treeverse, Inc. (Delaware, U.S. headquarters in Palo Alto) and Treeverse Labs Ltd. (Israel, engineering base) — and has raised $43M in total venture funding across a 2021 round led by Dell Technologies Capital, Norwest, and Zeev Ventures, and a July 2025 growth round led by Maor Investments. In November 2025 lakeFS acquired the DVC open-source project from Iterative.ai, extending its reach into individual data scientists and small teams and unifying the two leading open-source data version control communities.
lakeFS firmographics
Firmographics- Name
- lakeFS
- Legal name
- Treeverse, Inc.
- Website
- https://lakefs.io
- Company type
- Private
- Founded year
- 2021
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Short description
- lakeFS (Treeverse, Inc.) provides Git-like data version control for S3-compatible object storage-based data lakes, serving enterprise AI, ML, and data engineering teams at organizations such as Arm, Lockheed Martin, Volvo, and NASA with zero-copy branching, atomic merges, and AI-ready data governance.
- Ownership category
- akta.pro rank
lakeFS industry classification
Industry- Product category
- Data Version Control / Data Lake Management
- NAICS
- Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (5182), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518210), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821)
- SIC
- Services-Computer Programming, Data Processing, Etc. (7370), Services-Computer Processing & Data Preparation (7374)
- akta.pro primary industry
- Lakehouse Platforms (HDAEABAB)
- akta.pro secondary industries
- Cloud Data Warehouses (HDAEABAA), Data Lake Platforms (HDAEABAC), Data Warehouse/Lakehouse Performance Optimization & Cost Management (HDAEABAL), Data & Analytics Platforms (Data Warehousing, Lakes, Streaming) (HDABAAAF), Object Storage Platforms (HDABAEAC)
Keywords
Where lakeFS is headquartered
LocationHeadquarters
- HQ city
- Santa Monica
- HQ country
- United States
- HQ region
- North America
Offices2 records
Markets served
lakeFS business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Operations, Infrastructure
Revenue model
- Open-source software (community edition): Free, Apache-licensed open-source lakeFS distributed via GitHub (treeverse/lakeFS), serving as the funnel for adoption; not a direct revenue stream but drives community and developer adoption.
- lakeFS Cloud (hosted SaaS): Managed lakeFS cloud offering promoted on the website ('Try lakeFS', 'lakeFS Cloud') as an alternative to self-hosted deployment, expected to be subscription-based with no public price list.
- lakeFS Enterprise (self-managed): Enterprise edition of lakeFS with additional features (RBAC, SSO, advanced hooks, monitoring/auditing, transactional mirroring, lakeFS Mount, managed GC) sold via a 'Contact Sales' / 'Book a Demo' sales motion to large enterprises and government.
- Venture funding and growth capital: Backed by venture funding ($23M in 2021 plus $20M growth round in 2025, totaling $43M) led by Maor Investments, Dell Technologies Capital, Norwest, and Zeev Ventures to fund engineering and go-to-market expansion.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Pay-as-you-go | Free open-source lakeFS (Apache 2.0) |
| Freemium | Pay-as-you-go | Free trial of lakeFS Cloud |
| Subscription | Multi-year contract | lakeFS Enterprise / Self-managed - quote-based |
Go-to-market motion4 records
Distribution channels5 records
Marketing channels12 records
lakeFS product offering
Product offeringCore offering
lakeFS is a Git-like data version control platform that sits on top of S3-compatible object storage, providing repositories, branches, commits, merges, tags, and zero-copy branching for petabyte-scale data lakes. It is sold as an Apache 2.0 open-source edition, a managed lakeFS Cloud SaaS, and a self-managed lakeFS Enterprise edition with RBAC, SSO, advanced hooks, and audit features. Customers include Fortune 100 enterprises and government research organizations managing data lakes for AI/ML and analytics workloads.
Differentiator
Problem solved
Functional benefit
Brands
- DVC (Data Version Control): Open-source data version control project acquired by lakeFS from Iterative.ai in November 2025; continues to operate as an open-source project under lakeFS stewardship.
- lakeFS Cloud
- lakeFS Enterprise
Quantifiable outcome
- Reduced testing time by 80% on two different projects within days of migrating to lakeFS data branching
- +4 more outcomes
Companies that use lakeFS
Customer profileNamed customers14 records
Segments4 records
Ideal customer profiles3 records
lakeFS technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration65 records
Feature10 records
lakeFS partnerships and signals
Strategic signalPartnerships
30 partnerships are on record, tiered core ecosystem partner, core integration, core integration (beta), strategic co-marketing partner, strategic partner and customer + ecosystem.
- Iterative.aicore ecosystem partnerlakeFS acquired the DVC open-source project from Iterative.ai in November 2025, taking over stewardship and continued maintenance of DVC as an open-source project with ongoing community support; unifies the two leading data version control communities.
- Databrickscore integrationlakeFS integrates with Databricks (Spark, Delta Lake, Unity Catalog, Databricks LiveTables, and Databricks AI Functions) to provide versioned data access to Databricks notebooks, jobs, and SQL warehouses.
- Snowflakecore integration (beta)lakeFS lists Snowflake as a supported (Beta) compute engine, enabling data warehousing workloads to read versioned data managed by lakeFS.
- Amazon Web Servicescore integrationlakeFS supports AWS S3 object storage, AWS Glue, AWS Athena, AWS EMR, AWS Kinesis, AWS Kinesis Data Streams, AWS SageMaker, and AWS IAM roles for authentication; S3 integration is documented as a primary deployment target.
- Google Cloudcore integrationlakeFS integrates with Google Cloud Storage, GCP DataProc, and GCP PubSub as supported storage, compute, and ingest targets, with documentation at docs.lakefs.io/deploy/gcp.html.
- Microsoft Azurecore integrationlakeFS supports Azure Blob Storage, Azure ADLS, and Azure Synapse (via Microsoft Learn partner documentation) as supported object storage and compute engines.
- Apache Sparkcore integrationlakeFS is a supported integration with Apache Spark, enabling Spark jobs to read and write versioned data through the lakeFS Spark client.
- Presto / Trinocore integrationlakeFS supports both Presto and Trino (plus Starburst Galaxy) as query engines, with version-aware query routing over lakeFS-managed data.
- Dremiostrategic co-marketing partnerlakeFS and Dremio co-published a tutorial demonstrating versioned multimodal AI data management combining lakeFS, Apache Iceberg, and Dremio for unified SQL and AI-powered unstructured data queries.
- Apache Icebergcore integrationlakeFS supports Apache Iceberg as a first-class open table format, including integration with the Iceberg REST Catalog.
- Delta Lakecore integrationlakeFS supports Delta Lake as a primary open table format for transactional table formats on top of object storage.
- Apache Kafkacore integrationlakeFS supports Apache Kafka as an ingest technology, enabling streaming data ingestion into versioned lakeFS repositories.
- Apache Flinkcore integrationlakeFS integrates with Apache Flink as a streaming ingest technology for versioned data lakes.
- Airbytecore integrationlakeFS lists Airbyte as a supported ingest technology, enabling ELT data to flow directly into versioned lakeFS repositories.
- Fivetrancore integrationlakeFS supports Fivetran connectors as an ingest path into versioned lakeFS repositories (referenced via Fivetran connector docs).
- Apache Airflowcore integrationlakeFS supports Apache Airflow natively with a dedicated Airflow Hook for orchestrating versioned data pipelines and pre-merge validations.
- Dagstercore integrationlakeFS supports Dagster as a supported orchestration and workflow engine for versioned data pipelines.
- Prefectcore integrationlakeFS supports Prefect via the community prefect-lakefs integration for orchestrating versioned data workflows.
- Kubeflowcore integrationlakeFS supports Kubeflow as a supported ML orchestration platform for MLOps pipelines operating on versioned data.
- MLflowcore integrationlakeFS supports MLflow, enabling experiment tracking and model registry metadata to be linked to versioned datasets in lakeFS.
- Amazon SageMakercore integrationlakeFS supports Amazon SageMaker for ML training and inference on versioned data.
- Weights & Biases (W&B)core integrationlakeFS supports W&B via the 'save-restore' guide so experiment runs and artifacts can be tied to versioned datasets in lakeFS.
- Hugging Facecore integrationlakeFS integrates with Hugging Face Datasets to load and version datasets used for model training.
- Vertex AIcore integrationlakeFS integrates with Google Vertex AI for ML training and inference on versioned data.
- Red Hat OpenShift AIstrategic partnerlakeFS is featured in Red Hat's OpenShift AI ecosystem as a data version control solution for AI workloads, including speaker participation from Red Hat at the AI-Ready Data Summit.
- LanceDBcore integrationlakeFS integrates with LanceDB as a vector database option for AI/ML workflows using versioned data.
- Great Expectationscore integrationlakeFS integrates with Great Expectations for data quality testing, typically invoked as pre-merge hooks in the lakeFS workflow.
- Monte Carlo Datacore integrationlakeFS integrates with Monte Carlo Data for data observability over versioned lakeFS repositories.
- NVIDIAstrategic partnerNVIDIA is displayed in the 'Our partners' logo strip on the lakeFS homepage, signaling a technology/computing partnership for AI workloads on versioned data.
- Amazon (re: broader Amazon AWS ecosystem partnership)customer + ecosystemAmazon is both a named enterprise customer logo on the lakeFS homepage and the provider of AWS services (S3, Glue, SageMaker, Kinesis, EMR) that lakeFS deeply integrates with as part of its commercial offering.
Scale indicators7 records
Recent moves6 records
Expansion highlights6 records
lakeFS competitors and assessment
Company assessmentDirect peers
- Pachyderm: Pachyderm is the closest direct competitor to lakeFS, offering Git-like data versioning and data lineage on top of object storage. It targets the same enterprise data engineering and ML teams with petabyte-scale lake workloads, making it a head-to-head rival for data version control spend.
- Iterative.ai (DVC): Iterative.ai created DVC, the open-source data version control project lakeFS acquired in November 2025. It is the most comparable project on a functional basis and was a direct competitor prior to the acquisition; DVC still operates as an open-source community.
Broad incumbents
- Databricks (Unity Catalog): Databricks bundles Unity Catalog for data governance and versioning into its lakehouse platform. It overlaps with lakeFS on data governance and lineage for Delta Lake customers, but as part of a much broader data + AI platform rather than a specialized version-control layer.
- Snowflake (Horizon Catalog): Snowflake has expanded into governance and data versioning via Horizon Catalog. It is a broad incumbent in cloud data warehousing that competes with lakeFS for governance and lineage budget on top of shared storage, and is a supported (BETA) integration partner for lakeFS as well.
- Alation: Alation is a data catalog and governance platform used by enterprises alongside lakeFS. It addresses adjacent parts of the data trust stack (cataloging, lineage) and competes for some of the same governance budget lakeFS targets.
Emerging players
- Monte Carlo Data: Monte Carlo is a data observability platform that addresses a portion of the same problem lakeFS solves (trust in production data via quality and lineage signals). It integrates with lakeFS via pre-merge hooks, indicating overlapping but complementary positioning.
- Great Expectations: Great Expectations is the leading open-source data quality testing framework and is invoked as a pre-merge hook in lakeFS workflows. It competes for the data-testing and validation portion of the data engineering stack lakeFS also targets.
- Dremio: Dremio is an open lakehouse platform that supports Iceberg and queries versioned data. It is a co-marketing partner with lakeFS and an overlapping solution for SQL-on-versioned-data lake workloads.
- Weights & Biases: Weights & Biases provides ML experiment tracking and dataset versioning, partially overlapping with lakeFS's ML-experiments use case and DVC's historical positioning. It is a supported integration and adjacent competitor for ML-practitioner versioning budget.
Others
- Apache Iceberg: Apache Iceberg is an open table format that provides schema evolution and time-travel features, overlapping with a subset of lakeFS's version control value proposition. Iceberg is also a core integration partner, blurring the line between competitor and ecosystem component.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks6 records
Key highlights7 records
Customer concentration
lakeFS social profiles
Digital presencelakeFS financial estimates
Financial estimateRevenue estimate
Valuation estimate
lakeFS leadership team
Management profileNumber of profiles
Profiles3 records
lakeFS subsidiaries and ownership
Company hierarchySubsidiaries1 record
lakeFS funding detail
Funding detailFunding overview
Funding rounds2 records
Investors4 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
lakeFS M&A and investment
M&A and investmentM&A1 record
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about lakeFS
What does lakeFS do?
lakeFS is a Git-like data version control platform that sits on top of S3-compatible object storage, providing repositories, branches, commits, merges, tags, and zero-copy branching for petabyte-scale data lakes. It is sold as an Apache 2.0 open-source edition, a managed lakeFS Cloud SaaS, and a self-managed lakeFS Enterprise edition with RBAC, SSO, advanced hooks, and audit features. Customers include Fortune 100 enterprises and government research organizations managing data lakes for AI/ML and analytics workloads.
Is lakeFS a public or private company?
lakeFS is a private company. It is classified as venture growth investor backed and is currently operating.
When was lakeFS founded?
lakeFS was founded in 2021. It employs 11 to 50 people.
Where is lakeFS based?
lakeFS is headquartered in Santa Monica, United States, in the North America region.
How does lakeFS make money?
Four revenue lines are on record. Open-source software (community edition) is the primary driver. The others are lakeFS Cloud (hosted SaaS), lakeFS Enterprise (self-managed) and venture funding and growth capital.
Who are lakeFS's main competitors?
Direct peers on record are Pachyderm and Iterative.ai (DVC). Broad incumbents are Databricks (Unity Catalog), Snowflake (Horizon Catalog) and Alation. Emerging players are Monte Carlo Data, Great Expectations, Dremio and Weights & Biases. Apache Iceberg is listed as an others.
Does lakeFS have an API?
Yes. lakeFS offers a comprehensive set of APIs for managing data version control operations, including the lakeFS HTTP REST API, lakectl command-line interface, S3 Gateway API, Authorization API, and a Spark Client. The APIs enable developers to create branches, commits, tags, and manage repositories on object storage. Python SDK (including a High-Level SDK) is provided, along with Boto/S3 Gateway support and integration with AWS CLI. APIs support both the open-source and Enterprise editions. Developer documentation is at docs.lakefs.io/reference/api.
What industry is lakeFS in?
lakeFS's product category is Data Version Control / Data Lake Management. Its primary akta.pro industry code is HDAEABAB, Lakehouse Platforms, with a secondary code of HDAEABAA, Cloud Data Warehouses. Its NAICS code is 518 and its SIC code is 7370.