lakeFS Acquires DVC, Uniting Data Version Control Pioneers to Accelerate AI-ready Data
Foundational technology for enterprise AI success now ranges from individual data science projects to Fortune 100 AI infrastructure
With this acquisition, lakeFS will take on stewardship of the DVC open source project. DVC, an early pioneer of the data version control category, will continue as an independent open source tool focused on data scientists working with smaller datasets, while lakeFS will continue to advance enterprise-grade data version control infrastructure for organizations managing AI and ML at scale.
"Data version control has become a foundational technology for enterprise AI success. Building on top of our enterprise-scale data version control engine, lakeFS is the control plane for AI-ready data, providing infrastructure for data quality, data provenance and unified data access," said Dr.
This acquisition builds on lakeFS's recent momentum, including its
Accelerating Enterprise AI Through Data Version Control
The combination comes at a critical time for enterprise AI adoption. According to an EY survey on AI adoption, 83% of executives report that AI adoption would be faster with stronger data infrastructure, while 67% cite the lack of data infrastructure as the primary barrier to AI progress. Data version control has emerged as a foundational requirement for managing the massive, evolving datasets that power modern AI initiatives.
"We're thrilled that the DVC community has found a new home with lakeFS," said
Looking ahead, this acquisition will strengthen the open source data version control ecosystem by combining resources, expertise, and community engagement across both projects. To learn more about today's news, register for our webinar on December 3 at
Resources
- Webinar on December 3: A New Chapter for DVC: Passing the Torch to lakeFS
- Download lakeFS OSS at lakefs.io
- Explore lakeFS Enterprise at lakefs.io/enterprise
- Download DVC for Git at dvc.org
DVC Git extension for data scientists:
DVC serves as the easy-to-use Git extension for data version control, designed specifically for data scientists working on single projects with smaller datasets. As a lightweight tool, DVC enables individual practitioners to apply version control best practices to their data science workflows with minimal overhead.
lakeFS, the control plane for AI ready data, ideal for AI and data engineering teams:
lakeFS is the control plane for AI-ready data, bridging the infrastructure gap that slows down enterprise AI initiatives. Built on a highly scalable data version control architecture, lakeFS manages the data lifecycle, governance, and unified access to AI-ready data. Designed for complex AI operations and big data environments with petabyte-scale multimodal data lakes, lakeFS offers the scalability, high performance, and seamless integration with enterprise data ecosystems that AI, MLOps, data engineering and data science teams need in order to tackle their most complex challenges.
About lakeFS
lakeFS is the control plane for AI-ready data, bridging the infrastructure gap that slows down enterprise AI initiatives. Built on a highly scalable data version control architecture, lakeFS manages the data lifecycle, governance, and unified access to AI-ready data. This approach accelerates AI delivery, ensures reproducibility, reduces data friction, and supports compliance across data silos. lakeFS is trusted by AI/MLOps teams, data engineers, and data scientists at thousands of organizations including Arm, Bosch, Lockheed Martin, NASA, Volvo, and the U.S. Department of Energy. Learn more at lakefs.io.
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SOURCE lakeFS
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