AWS athena documentation change
Summary
Added November 21, 2025 release notes with 12 new features including Spark integration, capacity controls, Iceberg optimizations, security enhancements with Lake Formation, JWT authentication support, and driver updates
Security assessment
The change adds documentation about security features including Spark Connect secure cluster interaction, Lake Formation table-level access controls, and JWT trusted identity propagation authentication. However, there is no indication these changes address existing vulnerabilities or security incidents - they document new security capabilities rather than fix issues.
Diff
diff --git a/athena/latest/ug/release-notes.md b/athena/latest/ug/release-notes.md index 146fc40c1..d785e76c1 100644 --- a//athena/latest/ug/release-notes.md +++ b//athena/latest/ug/release-notes.md @@ -35,0 +36,39 @@ Describes Amazon Athena features, improvements, and bug fixes by release date. +### November 21, 2025 + +Published on 2025-11-21 + +Athena announces the following features and improvements. + + * **Amazon Athena for Apache Spark is now available in notebooks** – Provides data engineers, analysts, and data scientists with a unified workspace to query data, develop jobs, train models, and work with AI. Athena for Apache Spark runs on Spark 3.5.6 and has new debugging features, real-time monitoring through Spark UI, Spark Connect for secure cluster interaction, and AWS Lake Formation table-level access controls. Learn more at the [SageMaker user guide](https://docs.aws.amazon.com/sagemaker-unified-studio/latest/userguide/notebooks.html). + + * **Capacity Reservations cost and performance controls** – You can now set Data Processing Unit (DPU) usage limits at the workgroup or query level and get DPU usage details for queries that you run on Capacity Reservations. These controls help you fine-tune query performance and manage costs by controlling resource usage for your most important SQL workloads. To learn more, see [Control capacity usage](./capacity-management-control-capacity-usage.html). + + * **Capacity Reservations auto-scaling solution** – You can now automatically adjust Capacity Reservations based on utilization. Athena's solution uses CloudFormation and Step Functions to remove the need for manual capacity adjustments, helping you balance performance requirements with cost optimization, and is customizable for different needs. To learn more, see [Automatically adjust capacity](./capacity-management-automatically-adjust-capacity.html). + + + + + * **Optimization with Iceberg statistics** – Athena has enhanced how it uses Iceberg statistics to make intelligent decisions about join ordering, filters, and aggregation behavior that can improve query performance and reduce costs. To learn more, see [Use Iceberg table statistics](https://docs.aws.amazon.com/athena/latest/ug/capacity-management-automatically-adjust-capacity.html). + + * **Iceberg Parquet column indexing** – Athena now supports Parquet column indexing on Iceberg tables for precise data pruning during query execution. It leverages page-level min/max statistics to reduce the amount of data scanned, improving query performance and lowering costs, particularly for queries with selective filter predicates on sorted columns. To learn more, see [Use Parquet column indexing](https://docs.aws.amazon.com/athena/latest/ug/querying-iceberg-data-optimization.html). + + * **Iceberg performance enhancements with Lake Formation** – Athena has added new partition pruning behaviors for Iceberg tables that have Lake Formation row filters and column masks, and additional predicate pushdown behaviors for all other table types that have Lake Formation row filters and column masks. This update enhances query performance while maintaining security protections. + + * **Query result reuse** – Athena has improved query result reuse to enable more queries to benefit from cached results. Athena now treats semantically equivalent queries as identical regardless of formatting differences. Customers who use query result reuse will automatically benefit from increased cache hit rates, resulting in faster query execution and reduced costs, with no action needed. To learn more, see [Reuse query results in Athena](https://docs.aws.amazon.com/athena/latest/ug/reusing-query-results.html). + + * **Upgraded data lake file SerDes** – Athena has upgraded its SerDes for Parquet, JSON, CSV, and text files. This improves query performance and reliability while correcting for scenarios where previous SerDes returned non-deterministic or incorrect results. Customers will automatically benefit from these improvements without any action needed as they are upgraded based on compatibility checks performed by Athena. + + + + + * **Hudi 0.15.0 upgrade** – You can now use Athena to query Hudi 0.15.0 tables. For more information, see [Query Apache Hudi datasets](https://docs.aws.amazon.com/athena/latest/ug/querying-hudi.html). + + * **Browser trusted identity propagation integration** – Athena added a new authentication plugin to support JWT trusted identity propagation integration with JDBC and ODBC drivers. This authentication type allows you to fetch a JSON web token (JWT) from an external identity provider and authenticates with Athena. For more information, see [Use Trusted identity propagation with Amazon Athena drivers](./using-trusted-identity-propagation.html). + + * **JDBC 3.7.0 driver** – Athena releases JDBC driver version 3.7.0. For more information about this version of the driver, see [Amazon Athena JDBC 3.x release notes](./jdbc-v3-driver-release-notes.html). To download the latest JDBC driver, see [JDBC 3.x driver download](./jdbc-v3-driver.html#jdbc-v3-driver-download). + + * **ODBC 2.0.6.0 driver** – Athena releases ODBC driver version 2.0.6.0. For more information about this version of the driver, see [Amazon Athena ODBC 2.x release notes](./odbc-v2-driver-release-notes.html). To download the latest JDBC driver, see [ODBC 2.x driver download](./odbc-v2-driver.html#odbc-v2-driver-download). + + + + @@ -1206 +1245 @@ Published on 2022-11-30 -You can now interactively create and run Apache Spark applications and Jupyter compatible notebooks on Athena. Run data analytics on Athena using Spark without having to plan for, configure, or manage resources. Submit Spark code for processing and receive the results directly. Use the simplified notebook experience in Amazon Athena console to develop Apache Spark applications using Python or [ Use Athena notebook APIs](./notebooks-spark-api-list.html). +You can now interactively create and run Apache Spark applications and Jupyter compatible notebooks on Athena. Run data analytics on Athena using Spark without having to plan for, configure, or manage resources. Submit Spark code for processing and receive the results directly. Use the simplified notebook experience in Amazon Athena console to develop Apache Spark applications using Python or [ Use Athena Spark APIs](./notebooks-spark-api-list.html).