AWS Database Migration Service (AWS DMS) now supports Amazon Timestream, as a target endpoint. With this new support, you can securely migrate your time series data to Amazon Timestream, where you can store, process, and derive business insights cost-effectively. 

AWS Supply Chain Demand Planning now offers a quicker and thus more user-friendly way to execute key workflows, such as displaying a forecast view based on given selected filters to refine the forecast. By improving database indexing and query performance, AWS Supply Chain Demand Planning delivers up to 75% lower read latencies. With this release, AWS Supply Chain Demand Planning also introduced upgrades to it forecasting capabilities to enable faster model training and predictions, resulting in up to 3x faster forecast generation than previous versions.

Today, we are excited to announce that customers using IAM Identity Center as their authentication method in SageMaker Studio can now fully automate setup of Studio user profiles using SageMaker and IdC APIs.

Amazon Relational Database Service (RDS) for PostgreSQL now supports the latest minor versions PostgreSQL 15.5, 14.10, 13.13, 12.17, and 11.22. We recommend that you upgrade to the latest minor versions to fix known security vulnerabilities in prior versions of PostgreSQL, and to benefit from the bug fixes, performance improvements, and new functionality added by the PostgreSQL community. With this release, RDS for PostgreSQL now supports pgactive extension starting with PostgreSQL major versions 11 and higher.

Amazon DocumentDB (with MongoDB compatibility) is now available in the AWS GovCloud (US-East) Region adding to the list of available regions where you can use Amazon DocumentDB. AWS GovCloud (US) Regions are isolated AWS Regions designed to host sensitive data and regulated workloads in the cloud, assisting customers who have United States federal, state, or local government compliance requirements.

AWS Glue for Apache Spark now supports native connectivity to Amazon OpenSearch Service which enables users to efficiently read and write data from Amazon OpenSearch Service without the need to install or manage OpenSearch connector libraries. Users can now use data stored in OpenSearch Service indexes as a source or target within AWS Glue Studio’s no-code, drag-and-drop visual interface or directly in an AWS Glue ETL job script. When combined with AWS Glue’s ETL (Extract, Transform, Load) capabilities, this new connector simplifies the creation of ETL pipelines enabling ETL developers to save time building and maintaining data pipelines.

We are excited to announce general availability of AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs) with Amazon EMR on EC2 clusters. With today’s launch, Amazon EMR simplifies security and governance over transactional data lakes by providing access controls at table, column and row level permissions with your Apache Spark jobs accessing Apache Iceberg, Apache Hudi and Delta tables.

AWS Glue for Apache Spark announces the launch of six new database connectors: Teradata, SAP HANA, Azure SQL, Azure Cosmos DB, Vertica, and MongoDB. These native connectors enable users to efficiently read and write data from these systems without the need to install or manage any connector libraries. Users can add these databases as a source or target within AWS Glue Studio’s no-code, drag-and-drop visual interface or use the connector directly in an AWS Glue ETL script job.

Amazon Relational Database Service (Amazon RDS) Custom for SQL Server now allows customers to use SQL Server Developer Edition by providing their own SQL Server Developer Edition installation media when creating an instance. Utilizing Developer Edition allows customers to lower the cost of development and testing with Amazon RDS Custom for SQL Server. Amazon RDS Custom is a managed database service that allows customization of the underlying operating system and database environment. Features of RDS Custom for SQL Server include Multi-AZ deployment, BYOL using Bring-Your-Own-Media and more. 

Amazon S3 Storage Lens now provides request metrics for prefixes within an S3 bucket. Prefix-level metrics like total request counts, request counts by status code, bytes downloaded, and more, help you better understand activity for the largest prefixes within a bucket, and identify opportunities to optimize your S3 storage.