AWS Glue now supports Apache Iceberg based materialized views
AWS Glue now supports materialized views, a new capability that makes it easier for data teams to transform data and accelerate query performance. Materialized views are managed tables in the AWS Glue Data Catalog that store precomputed query results in Apache Iceberg format and automatically keep them up to date as source data changes. This feature is designed to make it easy for data engineers and analytics teams to transform data through multiple stages, from raw data to final analytical tables while reducing engineering effort and operational overhead.
Customers can now create materialized views using standard Spark SQL syntax with a data refresh schedule. The service automatically handles the refresh schedule, change detection, incremental updates, and compute infrastructure management. Spark engines across Amazon Athena, Amazon EMR, and AWS Glue intelligently rewrite queries to use these materialized views, accelerating performance by up to 8x while reducing compute costs. You can use SQL query engines like Athena and Redshift to access the materialized views as Iceberg tables from SQL editors and Amazon SageMaker notebooks.
Materialized views in AWS Glue are available in Europe (Stockholm), Asia Pacific (Thailand), Asia Pacific (Mumbai), Europe (Paris), US East (Ohio),Europe (Ireland), Europe (Frankfurt), South America (Sao Paulo), Asia Pacific (Hong Kong), US East (N. Virginia), Asia Pacific (Seoul), Asia Pacific (Malaysia), Europe (London), Asia Pacific (Tokyo), US West (Oregon), US West (N. California), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central), and Europe (Spain). To learn more, visit Working with Materialized Views in the AWS Glue developer guide.