Releasesby Ibis
Amazon EMR on EKS reduces EMR charge by 30 percent
UpdateyesterdayUnverifiedAdded Oct 24, 2026
Amazon EMR announces a reduction of 30 percent in the EMR charge added to EKS when running EMR on EKS. This price decrease applies to both the per-vCPU-hour charge and the per-GB-hour charge, while the underlying Amazon EKS charges remain unchanged. All EMR workloads running on the EKS deployment option benefit from this change.
More Amazon Athena and EMR releases
Every Amazon Athena and EMR releaseAmazon 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.
Also shipped on Oct 23, 2026
AWS in October 2026Retrieve Cortex Search (Public Preview)
The CORTEX_SEARCH_RETRIEVE table function is now in public preview, allowing users to execute low-latency search queries directly from SQL for RAG and chatbot applications.
DataFrame caching on serverless compute is now in Public Preview
Databricks now supports DataFrame caching on serverless compute via df.cache() or df.persist(), allowing users to reuse results within a session.
Box Audit Logs managed ingestion connector (Beta)
The Box Audit Logs connector for Lakeflow Connect is now available in beta, enabling the ingestion of enterprise audit events into Databricks.
Manage Test Engine workflows with Terraform and the REST API
Users can now manage Test Engine workflows using the buildkite_test_suite_workflow Terraform resource or the REST API, enabling code-based configuration of monitors and actions.
Flagship - Target Flagship feature flags with structured evaluation context
Flagship now supports nested objects and arrays in evaluation context, allowing developers to target feature flags based on complex user profiles and tags.
Responses API for the Cortex REST API (Preview)
The new Responses API in the Cortex REST API provides OpenAI-compatible endpoints for accessing models.