Sold by: lakeFS
Deployed on AWS
lakeFS transforms object storage buckets into data lake repositories that expose a Git-like interface. By design, it works with data of any size.
The Git-like interface means users of lakeFS can use the same development workflows for code and data. Git workflows greatly improved software development practices; we designed lakeFS to bring the same benefits to data.
With lakeFS Cloud, enjoy all the benefits of a Git-like version control interface for your data lake, in a fully managed service. No deployment, installing, maintaining and scaling overhead.
Overview
lakeFS is the control plane for AI data. It provides Git like version management and governance for object stores, giving data and AI teams a reliable foundation for building and operating large scale, production grade AI systems. lakeFS solves the core challenges of managing fast changing, high volume data by creating a consistent and programmable layer on top of your data lake. This enables organizations to bring order, predictability, and automation to the full lifecycle of AI data.
With lakeFS, teams create isolated data branches to test feature engineering, retrain models, or run analytics without disrupting production datasets. Every change to data is atomic and reversible, allowing safe iteration, continuous experimentation, and predictable promotion of validated data to production. lakeFS turns any object store into a structured environment with commits, merges, rollbacks, and lineage, enabling full reproducibility and control across all AI and analytics workflows.
lakeFS works as a scalable, low overhead control plane that integrates with existing compute engines, pipelines, and governance tools. It supports Spark, Python, Hive, Presto, Flink, and modern AI and ML workload patterns. Because it runs on top of S3 compatible storage, lakeFS requires no changes to the underlying data layout and can operate at the scale of enterprise and hyperscale data platforms.
Key capabilities include zero copy branching for isolated model training and data preparation, reproducible data snapshots for compliance and auditing, automated checks that validate data before merging, and instant rollback to recover from bad data, pipeline failures, or unintended model drift. lakeFS ensures every version of your AI data is tracked, discoverable, and available for debugging, analysis, and governance.
By using lakeFS as the control plane for AI data, organizations increase the quality and velocity of model development, reduce incidents caused by bad data, and achieve reliable and explainable AI behavior. lakeFS brings a modern software development lifecycle to data, enabling consistent, trustworthy, and governed AI operations at scale.
For custom pricing, EULA, or a private contract, please contact AWS-Marketplace@treeverse.com , for a private offer.
Highlights
- Data teams efficiency - eliminates repetitive manual tasks such as manual rollback of production data or data reproducibility. Save data engineers time by automation.
- High quality data product - validate the data coming into or analyzed within the lake before it is exposed to external users, taking advantage of a CI/CD pipeline for your data, preventing inconsistencies and error.
- Data resilience - quickly recover from mistakes / inconsistencies by rolling back the entire data lake to its previous consistent state.
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
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Dimension | Description | Cost/12 months |
|---|---|---|
lakeFS Managed Service | Git-like version control for a data lake, in a fully managed service. Includes 500,000 annual API Calls. | $85,000.00 |
Dimensions summary
You buy lakeFS Cloud through a single contract dimension: the lakeFS Managed Service, priced by unit. Each unit gives you Git-like version control for a data lake in a fully managed service. It includes 500,000 API calls per year. To scale usage, you add more units. Pricing grows with the number of units you commit to, not with separate tiers or feature levels. This is the only pricing option on Marketplace.
Top-of-mind questions for buyers
Each interaction with the lakeFS Managed Service through its interface counts as an API call. This includes operations like creating branches, committing data, merging, and rolling back. High-frequency workflows such as automated pipelines and agent runs consume these calls faster than manual, occasional use.
The included 500,000 annual API calls come with each unit. To support more usage, you commit to additional units, which each add their own call allowance. The specific handling of calls beyond your committed units is not detailed here, so contact the vendor for overage terms.
No. Your data and metadata stay in your own storage. The managed service tracks pointers to file locations per commit, and those pointers also sit inside your buckets. Zero-copy branches let teams work in isolated environments without duplicating data or adding storage cost.
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Reach support through email or within lakeFS cloud chat on https://lakefs.cloud Email support, contact us through our website, or report an issue on the built-in chat in the product.
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