Accelerate data lake operations with Apache Iceberg V3 deletion vectors and row lineage In this post, we walk you through the new capabilities in Iceberg V3, explain how deletion vectors and row lineage address these challenges, explore real-world use cases across industries, and provide practical guidance on implementing Iceberg V3 features across AWS analytics, catalog, and storage services.
https://aws.amazon.com/blogs/b....ig-data/accelerate-d

Introducing catalog federation for Apache Iceberg tables in the AWS Glue Data Catalog AWS Glue now supports catalog federation for remote Iceberg tables in the Data Catalog. With catalog federation, you can query remote Iceberg tables, stored in Amazon S3 and cataloged in remote Iceberg catalogs, using AWS analytics engines and without moving or duplicating tables. In this post, we discuss how to get started with catalog federation for Iceberg tables in the Data Catalog.
https://aws.amazon.com/blogs/b....ig-data/introducing-

Achieve 2x faster data lake query performance with Apache Iceberg on Amazon Redshift In 2025, Amazon Redshift delivered several performance optimizations that improved query performance over twofold for Iceberg workloads on Amazon Redshift Serverless, delivering exceptional performance and cost-effectiveness for your data lake workloads. In this post, we describe some of the optimizations that led to these performance gains.
https://aws.amazon.com/blogs/b....ig-data/achieve-2x-f

Medidata’s journey to a modern lakehouse architecture on AWS In this post, we show you how Medidata created a unified, scalable, real-time data platform that serves thousands of clinical trials worldwide with AWS services, Apache Iceberg, and a modern lakehouse architecture.
https://aws.amazon.com/blogs/b....ig-data/medidatas-jo

Run Apache Spark and Apache Iceberg write jobs 2x faster with Amazon EMR In this post, we demonstrate the write performance benefits of using the Amazon EMR 7.12 runtime for Spark and Iceberg compares to open source Spark 3.5.6 with Iceberg 1.10.0 tables on a 3TB merge workload.
https://aws.amazon.com/blogs/b....ig-data/run-apache-s