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Increase data quality and reduce the painful cost of errors
Transform your data lake into a Git-like repository
The lakeFS open source project for data lakes allows data versioning, rollback, debugging, testing in isolation, and more – all in one.
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Data versioning at scale
Our data is transient and dealing with it is an inefficient and manual task. With lakeFS,
your data lake is versioned and you can easily time-travel between consistent snapshots of the lake.
Develop on top of production
data, in isolation
Deploy data with confidence
Effective troubleshooting and
reverting in production
Works seamlessly with today’s data stack
Manage your data
like code
Your data stays in place while lakeFS provides highly scalable, format agnostic and zero copy git-like operations over it
Get Git-like operations for your data, with lakeFS
- Branches
Experiment
Instantly get a “copy” of your company’s data to debug or experiment
Test
Create an isolated snapshot of the data to debug issues
Collaborate
Work with your team on an isolated version of the data lake that you can all easily refer to
- Merges & Hooks
Best Practices & Data Quality
Expose changes to consumers after quality has been assured with pre-merge hooks
Version control
Create discoverable history of the data lake with an ordered set of versions, and ensure clear communication on which versions are used where
- Commits & Reverts
Rollback
Recover from errors by instantly reverting data to a former, consistent snapshot of the data lake
Troubleshoot
Investigate production errors by starting reproducing the state of the data at the time of failure
Stay updated
Data Engineering
Proudly announcing lakeFS Cloud
What is lakeFS? As data practitioners, we use many different terms to talk about what we do - we call it business...
Data Engineering
LakeFS Introduces a New Approach to Data Manageability and Reliability
lakeFS Cloud provides a Git-like repository for data lakes in a hosted version available in AWS Marketplace NEW YORK and TEL AVIV,...
Data Engineering
The State of Data Engineering 2022
A year has passed since we shared the State of Data Engineering 2021. And since we released that article last May, not...
