You can use lakeFS to manage data lakes using Git-like operations like branching, committing, and merging. It lets you create isolated data environments to test pipeline changes without copying underlying files. You can roll back erroneous data changes immediately to avoid breaking production workloads. The system tracks provenance and audit trails for machine learning training sets and AI workflows, ensuring reproducibility across runs. It connects directly with standard object stores and compute engines to maintain consistent data quality across your organization.
What lakeFS does
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Pricing model: Free trial
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