AWS Database Blog

Oracle Database@AWS (ODB@AWS) delivers Oracle Exadata infrastructure, managed by Oracle Cloud Infrastructure (OCI), directly within Amazon Web Services (AWS) data centers. In this post, we walk you through the backup and recovery options available for ODB@AWS services: Oracle Exadata Database Service on Dedicated Infrastructure (ExaDB-D) and Oracle Autonomous AI Database on Dedicated Exadata Infrastructure (ADB-D).

In this post, we show you how to optimize full-text search (FTS) performance in Amazon RDS for MySQL and Amazon Aurora MySQL-Compatible Edition through proper maintenance and monitoring. We discuss why FTS indexes require regular maintenance, common issues that can arise, and best practices for keeping your FTS-enabled databases running smoothly.

Amazon Aurora DSQL now supports PostgreSQL-compatible identity columns and sequence objects, so developers can generate unique integer identifiers with configurable performance characteristics optimized for distributed workloads. In distributed database environments, generating unique, sequential identifiers is a fundamental challenge: coordinating across multiple nodes creates performance bottlenecks, especially under high concurrency workloads. In this post, we show you how to create and manage identity columns for auto-incrementing IDs, selecting between identity columns and standalone sequence objects, and improving cache settings while choosing between UUIDs and integer sequences for your workload requirements.

In this post, you learn how to build a real-time AI movie recommendation system by streaming live data changes from Amazon Keyspaces to Amazon S3 vector storage. The post shows how to use Keyspaces change data capture streams to capture database modifications, convert them into vector embeddings using Amazon Bedrock, and store them in S3 Vector indexes for similarity searches that give AI applications access to fresh data within milliseconds.

Amazon DocumentDB 8.0 brings in support for MongoDB 8.0 API driver compatibility while maintaining support for applications built using MongoDB API versions 6.0 and 7.0. This post explores the new features in Amazon DocumentDB 8.0 and demonstrates how they improve performance and cost efficiency.

In this post, you learn how to implement conversational operations for Oracle E-Business Suite (Oracle EBS) on AWS by connecting Kiro CLI with your monitoring infrastructure through the MCP. We walk through the technical architecture that enables natural language queries to retrieve CloudWatch metrics, analyze logs, and execute operational commands.

In this post, we provide a guide to migrating from Redis OSS to ElastiCache for Valkey, incorporating different migration strategies and AWS best practices. Additionally, we highlight a customer’s successful migration to Valkey, which maintained their robust performance standards while achieving a 20% reduction in ElastiCache cluster costs.

You can use the AWS Database Migration Service Schema Conversion (AWS DMS SC) with generative AI feature to accelerate your database migration to AWS. This feature automatically handles the conversion of many database objects during migration by using traditional rule-based techniques and deterministic AI techniques. In this post, we demonstrate how Amazon Q Developer delivers generic solutions for complex AWS DMS SC issues, intelligently converts database stored procedure code from source to target database-compatible code, and automatically generates comprehensive test cases to validate your migrated database objects.

In this post, I introduce a framework for managing atomicity, consistency, isolation, and durability (ACID) compliant transactions in Amazon DynamoDB using C#, featuring support for nested transactions. This capability allows you to implement sophisticated logic with finer control over data consistency and error handling within your .NET applications. With this nested transaction framework, you can isolate issues, allow for partial rollbacks, and build maintainable, modular workflows on top of the built-in transactional capabilities of DynamoDB.

AWS has been named a Leader for the 11th consecutive year in the 2025 Gartner Magic Quadrant for Cloud Database Management Systems. And, once again, AWS has been positioned highest among all 20 evaluated companies for our Ability to Execute. We believe this reflects our ongoing commitment to giving customers the broadest and deepest set of capabilities to accelerate innovation as well as unparalleled security, reliability, and performance they can trust for their most critical applications.