AWS Database Blog

Amazon Web Services (AWS) users frequently use multiple accounts, organizing them efficiently with AWS Organizations. This system structures the accounts hierarchically and groups them into Organizational Units (OUs). However, this setup can sometimes add complexity, especially for teams that support the entire organization. Consider the following example of a database operations team’s predicament. Their task […]

Today, we are adding support for Valkey 8.0 on Amazon ElastiCache. ElastiCache version 8.0 for Valkey brings faster scaling for ElastiCache Serverless and memory optimizations for node-based clusters. In this post, we discuss these improvements and how you can benefit from them.

Today, Amazon RDS has announced support for MySQL version 8.4, which is the latest Long-Term Support (LTS) major version from the MySQL community. With that, Amazon RDS now supports MySQL Community Edition versions 8.0 and 8.4. In addition to the two community-supported LTS releases, Amazon RDS also offers MySQL 5.7 under RDS Extended Support, where RDS provides critical patches and bug fixes for the engine. For any of these versions, you can bring your existing MySQL code, applications, and tools to Amazon RDS. With MySQL 8.4, the MySQL community has introduced, as well as retired, multiple features, which are listed in the MySQL 8.4 reference manual. In this post, we explore some of these features, list known breaking changes, and provide recommendations to ease the migration of your workloads to this version.

Amazon Aurora Serverless v2 now supports scaling capacity down to 0 ACUs, enabling you to optimize costs during periods of database inactivity. Aurora Serverless is an on-demand, auto scaling configuration of Aurora that automatically adjusts your database capacity based on your workload requirements. Aurora Serverless measures database capacity in Aurora Capacity Units (ACUs) billed per second. 1 […]

Migrating an Oracle application and its underlying database to the cloud can be inherently complex. Complexity is significantly amplified by various factors, including operating system compatibility, database and application version, software availability, database storage technologies such as Automatic Storage Management (ASM), and stringent business downtime requirements. AWS Application Migration Service accelerates the migration of applications to Amazon Web Services (AWS) by automatically replicating entire servers at the block level. In this post, we show you the process of migrating Oracle E-Business Suite to AWS using Application Migration Service.

Aurora Limitless is a database solution that grows and shrinks vertically and horizontally with the current workload requirements. In this post, we show you how to test performance with the common tool pgbench. This tool is used with single-node database management systems (DBMS) and is optimized for single-node use cases. As we shall see in this post, this doesn’t mean that the tool measure what we think when it comes to multi-node systems. We demonstrate how it works with Aurora Limitless. We also discuss the obstacles and opportunities you might encounter when using this tool with Aurora Limitless.

In this post, we discuss how Coinbase migrated their user clustering system to Amazon Neptune Database, enabling them to solve complex and interconnected data challenges at scale.

Amazon DynamoDB is a serverless, NoSQL, fully managed database service that delivers single-digit millisecond latency at any scale. AWS recently announced the general availability of attribute-based access control (ABAC) for Amazon DynamoDB. ABAC is an authorization strategy that defines permissions based on attributes. In AWS, these attributes are called tags. You can attach tags to […]

PostgreSQL’s ability to handle concurrent access while maintaining data consistency relies heavily on its locking mechanisms, particularly at the row level. When multiple transactions attempt to lock the same row simultaneously, PostgreSQL turns to a specialized structure called MultiXact IDs. While MultiXacts provide an efficient way to manage multiple locks on a single row, they […]

This is the second post of a two-part series. In Part 1, we explored how you can use Automatic Data Optimization (ADO) and Oracle Information Lifecycle Management (ILM) policies for data compression. In this post, we demonstrate how to use Heat Map statistics to monitor data usage and integrate this information with hybrid partitioning and ILM data movement policies to move data to more cost-effective storage solutions.