Webinar-Lottie.svg

lakeFS Acquires DVC, Uniting Data Version Control Pioneers to Accelerate AI-Ready Data

webcros.svg
lakeFS Named Cool Vendor™ in the 2026 Gartner® Coolest Vendor Innovations in Data Management

Tutorials

Amazon EMR with lakeFS

Power Amazon EMR Applications with Git-like Operations Using lakeFS

This article will provide a detailed explanation of how to use lakeFS with Amazon EMR. Today, it’s common to manage a data lake using cloud

PebbleDB SSTable

Concrete Graveler: Committing Data to Pebble SSTables

Introduction In our recent version of lakeFS, we switched to base metadata storage on immutable files stored on S3 and other common object stores.

Working with Embed in Go

Working with Embed in Go 1.16 Version

The new Golang v1.16 embed directive helps us keep a single binary and bundle out static content. This post will cover how to work with

Building a data development environment

Building A Data Development Environment with lakeFS

Overview As part of our routine work with data we develop code, choose and upgrade compute infrastructure, and test new data. Usually, this requires running

Learn how to use lakeFS

The lakeFS Katacoda Sandbox Environment – Interactive Data Versioning Learning

If you’re interested in playing around and exploring lakeFS, you can now easily get started using the Katacoda demo which provides a personalized sandboxed environment

Caching in Go

In-process Caching In Go: Scaling lakeFS to 100k Requests/Second

This is a first in a series of posts describing our journey of scaling lakeFS. In this post we describe how adding an in-process cache

Getting Started

From Zero to Versioned Data in Spark

This tutorial aims to give you a fast start with lakeFS and use its git-like terminology in Spark. It covers the following: This simple flow

[hubspot type=form portal=8040338 id=9f5646ec-3e20-4568-9d6e-b82fca022065]