lakeFS Enterprise offers a fully standards-compliant implementation of the Apache Iceberg REST Catalog, enabling Git-style version control for structured data at scale. This integration allows teams to use Iceberg-compatible tools like Spark, Trino, and PyIceberg without any vendor lock-in or proprietary formats. By treating Iceberg tables as versioned entities within lakeFS repositories and branches, users […] The post Versioned Data with Apache Iceberg Using lakeFS Iceberg REST Catalog ap...| Git for Data – lakeFS
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, we focused on what it means for data teams: seamless, Git-like version control for structured and unstructured data, at any scale. But how did we […] The post How We Built Our lakeFS Iceberg Catalog appeared first on Git for Data - lakeFS.| Git for Data – lakeFS
An AI Factory with data versioning doesn't just run smoother. It fundamentally changes how teams interact with their data. Read more.| Git for Data - lakeFS
CANNES – Given all the tension surrounding consumers’ and brands’ expectations about customer experience and personalization, LiveRamp is betting that privacy-first approaches w...| Beet.TV - The Root to the Media Revolution
Discover what data discovery is, how it works, its benefits, challenges, and best practices to turn raw data into strategic, actionable insights.| Git for Data - lakeFS
Discover what an AI factory is, how it works, and how companies use it to turn raw data into scalable, automated, and intelligent business solutions.| Git for Data - lakeFS
Discover how multiple storage backends support in lakeFS provides a capability that unifies data management across all your storage systems.| Git for Data - lakeFS
AI data storage solutions are a key component of the modern AI landscape. Discover benefits, common challenges, and best practices. Read more| Git for Data - lakeFS