Category: MySQL compatible

In this post, we introduce the AWS Database Acceleration Toolkit (DAT), an open source database accelerator. DAT is an infrastructure as code solution using Terraform to simplify and automate initial setup, provisioning, and on-going maintenance activities for Amazon Aurora.

In this post, we discuss how to migrate MySQL very large databases (VLDBs) from a self-managed MySQL database to Amazon Aurora MySQL-Compatible Edition using the MyDumper and MyLoader tools.

On October 22, 2024, we announced the availability of the Aurora Global Database writer endpoint, a highly available and fully managed endpoint for your global database that Aurora automatically updates to point to the current writer instance in your global cluster after a cross-Region switchover or failover, alleviating the need for application changes and simplifying routing requests to the writer instance. In this post, we dive deep into the new Global Database writer endpoint, covering its benefits and key considerations for using it with your applications.

In this post, we focus on working with the features of mysql_fdw PostgreSQL extension on Amazon RDS for PostgreSQL to help manage a large set of data that on an external database scenarios. It enables you to interact with your MySQL database for importing individual/large/selectively number of objects at the schema level and simplifying how we get information about the MySQL/MariaDB schema, to make it easier to ultimately read/write data. We will also provide an introduction to understand query performance on foreign tables.

In the dynamic world of digital retail, performance, resilience, and availability are not only desirable qualities, they are essential. Recently, Dafiti, a leading fashion and lifestyle ecommerce conglomerate operating in Brazil, Argentina, Chile, and Colombia, undertook a significant transformation of its critical database infrastructure by migrating from self-managed MySQL Server 5.7 on Amazon EC2 to Amazon Aurora MySQL. This strategic move improved the resiliency and efficiency of its database operations. In this post, we show you why we chose Aurora MySQL-Compatible and how we migrated our critical database infrastructure.

This is the third post in a series where we dive deep into performance testing of MySQL environments being migrated from on premises. In Part 1, we compared the query playback and traffic mirroring approaches at a high level. In Part 2, we showed how to set up and configure query playback. In this post, we show you how to set up and configure traffic mirroring.

This is the second post in a series where we dive deep into performance testing MySQL environments being migrated from on premises. In Part 1, we compared the query playback and traffic mirroring approaches at a high level. In this post, we dive into the setup and configuration of query playback.

In this series of posts, we dive deep into performance testing of MySQL environments being migrated from on-premises to AWS. In this post, we review two different approaches to testing migrated environments with traffic that is representative of real production traffic: capturing and replaying traffic using a playback application, and mirroring traffic as it comes in using a proxy. This means you’re validating your environment using realistic data access patterns.

This post outlines a set of design and tuning strategies for a high-speed purge in an Amazon Relational Database Service (Amazon RDS) for MySQL DB instance and Amazon Aurora MySQL-Compatible Edition DB cluster. Purge is a housekeeping operation in a MySQL database. The InnoDB storage engine relies on it to clean up undo logs and delete-marked table records that are no longer needed for multiversion concurrency control (MVCC) or rollback operations.

Presence is a leading provider of live therapy and evaluation services for PreK-12 schools throughout the United States. Amazon RDS for MySQL has been a core part of Presence’s data architecture for many years. Presence used RDS read replicas, with replication filtering, to migrate applications from their centralized RDS for MySQL DB instance to dedicated DB instances. This approach allowed them to migrate each service, on its own schedule, with little downtime. In this post, we provide a practical example for migrating using the same method.