Releasesby Glyph
Amazon Athena introduces system tables for observability, auditing, and usage analytics
Amazon Athena now offers system tables which automatically capture your usage data and make it available for observability, usage analysis, and audit use cases. When you enable system tables, usage data is available within minutes of query completion across your workgroups and stored as service-managed, read-only Iceberg tables on Amazon S3 Tables with...
Also shipped Nov 9, 2026AWS in November 2026 →
The following AlloyDB AI features and improvements are generally available ( GA ): - Smart batching for AI...
The following AlloyDB AI features and improvements are generally available ( GA ): Smart batching for AI functions: AI function acceleration is generally available for ai.if , ai.rank , ai.analyze_sentiment , ai.summarize , ai.extract , ai.classify , and ai.generate on AlloyDB clusters running PostgreSQL 17 and later.
To support your FinOps practices, you can now opt in to compute cost attribution in BigQuery editions
To support your FinOps practices, you can now opt in to compute cost attribution in BigQuery editions. This feature attributes billed compute charges directly to the query projects that use your administration project's reservation capacity.
Query performance troubleshooting and job and system performance comparison in the BigQuery jobs explorer are...
Query performance troubleshooting and job and system performance comparison in the BigQuery jobs explorer are generally available (GA). For more information, see Troubleshoot job performance and Diagnose performance regressions by comparing jobs and systems .
When you create or schedule a pipeline, you can specify the maximum number of concurrently executed pipeline...
When you create or schedule a pipeline, you can specify the maximum number of concurrently executed pipeline tasks. This feature is generally available (GA).
You can use compression functions in GoogleSQL to compress or decompress bytes or string values by using the...
You can use compression functions in GoogleSQL to compress or decompress bytes or string values by using the Zstandard (Zstd) lossless data compression algorithm. The following functions are supported: ZSTD_COMPRESS ZSTD_DECOMPRESS_TO_BYTES ZSTD_DECOMPRESS_TO_STRING These functions are in Preview .
Fast mode for Anthropic Claude models is generally available
Fast mode for supported Anthropic Claude models, starting with Claude Fable 5.2 ( claude-fable-5-2 ), is available in General Availability (GA) . You can set "speed": "fast" in online pay-as-you-go prediction requests to accelerate output token generation for latency-sensitive agentic workflows.
More from Amazon Athena and EMREvery Amazon Athena and EMR release →
Amazon EMR on EKS reduces EMR charge by 30 percent
AWS has reduced the EMR charge for EMR on EKS workloads by 30 percent, applying to both per-vCPU-hour and per-GB-hour charges.
Amazon EMR Serverless now supports IPv6 and dual-stack connectivity
Amazon EMR Serverless now supports IPv6 and dual-stack connectivity, expanding beyond the IPv4-only connectivity that was previously available. You can now run your Apache Spark and Apache Hive jobs over IPv6 in your Amazon Virtual Private Cloud (VPC) by supplying dual-stack (IPv4 and IPv6) or IPv6-only subnets.
AWS Private CA now provides detailed certificate issuance logs
AWS Private CA announces detailed certificate issuance logs, a new AWS CloudTrail service event that records the complete certificate content, issuing CA information, requester identity, and signing status for every issuance.
Serverless Storage on Amazon EMR Serverless now supports terabyte-scale shuffle
Amazon EMR Serverless now offers enhanced serverless storage capabilities with support for up to 1TB shuffle operations, raising the previous 200 GB per-job limit. Amazon EMR Serverless makes it simple for data engineers and data scientists to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.
Amazon EMR on EKS now supports IPv6 Amazon EKS clusters
Today, AWS announces that Amazon EMR on EKS now supports running workloads on IPv6 Amazon Elastic Kubernetes Service (Amazon EKS) clusters. Amazon EMR on EKS enables data platform and analytics teams to run open-source big data frameworks such as Apache Spark and Apache Flink on Amazon EKS.
Amazon EMR introduces Long Term Support with Apache Spark 4.1
Amazon EMR introduces Long Term Support (LTS) releases, starting with emr-spark-8.1.0 and Apache Spark 4.1. With LTS, designated versions of the AWS runtime for Apache Spark receive 36 months of support. Amazon EMR provides LTS releases with fixes for critical and high severity security, bug, and data-corruption issues, subject to availability.
Amazon EMR 7.14 is now available
Amazon EMR 7.14 is now available with new features across Amazon EMR on EC2, Amazon EMR on EKS, and Amazon EMR Serverless, along with version upgrades for additional applications. This release also upgrades Apache Spark to 3.5.8 and Apache Iceberg to 1.10.1.