AWS Database Blog

In Amazon Relational Database Service (Amazon RDS) for SQL Server, database visibility is configured using a dedicated stored procedure. In this post, we demonstrate tenant isolation at the visibility level, preventing tenants from seeing database names belonging to other customers while maintaining their access to their own resources. This solution addresses an important architectural consideration in multi-tenant SQL Server environments where database names might reveal tenant information. By using the Amazon RDS for SQL Server custom stored procedure msdb.dbo.rds_manage_view_db_permission, users can effectively control database visibility on a per-login basis while maintaining full application functionality.

In this post, we discuss how the Shared Plan Cache feature of the Amazon Aurora PostgreSQL-Compatible Edition can significantly reduce memory consumption of generic SQL plans in high-concurrency environments.

Efficient storage management is crucial for maintaining the performance, reliability, and cost-effectiveness of your Oracle databases running on Amazon RDS. As your data grows and your workloads evolve, it’s essential to proactively monitor and optimize your storage utilization. In this post, we explore various techniques and best practices for effectively managing storage in RDS for Oracle Databases.

AWS Organizations now supports an upgrade rollout policy, a new capability that provides a streamlined solution for managing automatic minor version upgrades across your database fleet. This feature supports Amazon Aurora MySQL-Compatible Edition and Amazon Aurora PostgreSQL-Compatible Edition and Amazon RDS database engines MySQL, PostgreSQL, MariaDB, SQL Server, Oracle, and Db2. It eliminates the operational overhead of coordinating upgrades across hundreds of resources and accounts while validating changes in less critical environments before reaching production. In this post, we explore how upgrade rollout policy works, its key benefits, and how you can use it to implement a systematic approach to database maintenance across your organization.

In this post we show you how to build production-ready AI agents with durable state management using Amazon DynamoDB and LangGraph with the new DynamoDBSaver connector, a LangGraph checkpoint library maintained by AWS for Amazon DynamoDB.

In this post, we show you how to use additional storage volumes to expand your RDS for Oracle storage capacity beyond 64 TiB. In addition, we walk through use cases for additional storage volume and best practices while working with additional volumes.

In this post, we explain how to set up key components of Oracle Database@AWS offering including ODB network, Oracle Exadata infrastructure, Exadata VM clusters and Autonomous VM clusters using AWS CloudFormation template.

In this post, we show how you can enhance your Java application with the cloud-based capabilities of Amazon Aurora by using the JDBC Wrapper. Simple code changes shared in this post can transform a standard JDBC application to use fast failover, read/write splitting, IAM authentication, AWS Secrets Manager integration, and federated authentication.

Amazon Relational Database Service (Amazon RDS) for SQL Server now offers the Optimize CPU feature, which enabled control over vCPU allocation through core count modification setting. SQL Server licensing costs can consume a significant portion of your database budget, especially when you’re paying for vCPUs that aren’t fully utilized. This post demonstrates how to implement the Optimize CPU feature to potentially reduce licensing costs while maintaining performance for both new and existing Amazon RDS instances, along with performance benchmarking results and cost implications.

Applications using Aurora DSQL multi-Region clusters should implement a DNS-based routing solution (such as Amazon Route 53) to automatically redirect traffic between AWS Regions. In this post, we show you automated solution for redirecting database traffic to alternate regional endpoints without requiring manual configuration changes, particularly in mixed data store environments.