Building Compliant and Reproducible ML Pipelines

Itai Gilo
February 3, 2026

Based on my presentation at PyData Global 2025 When we – engineers – hear the word “compliance,” we tend to roll our eyes. We want to build features, not fill…

Iceberg REST Catalog Alternatives: Top Options & How to Choose The Best One For Your Team

Itai Gilo
January 19, 2026

Preparing data for AI projects is about more than fast storage or shiny new table formats – it all starts with selecting the right data catalog to anchor your entire…

Iceberg Tables Management: Processes, Challenges & Best Practices

Itai Gilo
December 17, 2025

We all love data lakes. They’re just perfect for storing massive volumes of structured, semi-structured, and unstructured data in native file formats. And they let us explore, refine, and analyze…

What is Iceberg Versioning and How It Improves Data Reliability

Itai Gilo
November 10, 2025

Apache Iceberg includes built-in table versioning to ensure that all changes to your data are logged, consistent, and recoverable. Instead of overwriting files or relying on task time, Iceberg saves…

How We Built Our lakeFS Iceberg Catalog

Itai Gilo
August 4, 2025

A behind-the-scenes look at the design decisions, architecture, and lessons learned while bringing the Apache Iceberg REST Catalog to lakeFS. When we first announced our native lakeFS Iceberg REST Catalog,…

Collaborating Over Data: Introducing Pull Requests in lakeFS

Oz Katz, Itai Gilo
October 21, 2024

In modern software development, Pull Requests (PRs) are a fundamental tool for collaborating on code. They allow teams to review, discuss, and merge changes in a controlled and transparent way. …