This article demonstrates how to query Apache Iceberg tables stored in Amazon S3 using Amazon Redshift, enabling transactionally consistent analytics on data lakes.

• Amazon Redshift now supports Apache Iceberg table format for read-only analytics queries
• Iceberg tables support schema and partition evolution without manual table alterations
• Redshift uses Iceberg metadata and column statistics to optimize query plans and reduce file scans
• Create external schemas in Redshift pointing to AWS Glue Data Catalog Iceberg tables
• Supports row-level updates and deletes with transactional consistency across Redshift and S3
• Enables unified views combining frequently accessed Redshift data with historical S3 data lake data
• Hidden partitioning automatically detects new partition values without manual updates
• Only Iceberg tables in AWS Glue Data Catalog supported; time travel queries not supported

Amazon Redshift's Iceberg support extends data warehouse capabilities to exabyte-scale data lakes, enabling cost-effective analytics with modern data lake operations and seamless schema evolution.