Category: MySQL compatible

Ola Money is a financial service provided by Ola Financial Services (OFS), which is part of the Ola group of companies. In this post, we share the modernization journey of Ola Money’s MySQL workloads using Amazon Aurora, a relational database management system built for the cloud with MySQL and PostgreSQL compatibility that gives the performance and availability of commercial-grade databases at one-tenth the cost.

As customers are migrating to the AWS Cloud to take advantage of managed database services such as Amazon RDS for MySQL, Amazon RDS for MariaDB, and Amazon Aurora MySQL-Compatible Edition, they also look to automate these administrative tasks. This post shows how a DBA or other user with access to a custom API can make MySQL and MariaDB backup requests. It uses Infrastructure as Code (IaC) with the AWS CDK to simplify the deployment.

Storage in Amazon Aurora MySQL is managed differently from traditional MySQL databases. In this post, we explore the different types of storage available in Amazon Aurora MySQL, how Aurora uses those storage types, and how to monitor storage consumption. We also explore some of the database queries and Amazon CloudWatch metrics for Aurora that you can use to estimate Aurora storage billing.

In this post, we show you how to set up bi-directional replication between an on-premises MySQL instance and an Aurora MySQL instance. We cover how to configure and set up bi-directional replication and address important operational concepts such as monitoring, troubleshooting, and high availability. In certain use cases, native bi-directional binary log replication can either provide a simpler fallback plan for your migration or provide a way to migrate applications or schemas individually, rather than all at the same time.

The binary log (binlog) in MySQL is used to capture database modifications on a MySQL server in a logical format known as “events”. These database modifications can include DCL statements (such as CREATE USER or GRANT), DDL statements (CREATE TABLE, ALTER TABLE) and DML statements (INSERT, UPDATE, DELETE). When such a modification is committed in […]

Because organizations store a large amount of their data in relational databases, there is a clear impetus to augment these datasets using generative artificial intelligence (AI) foundation models to elevate end-user experiences. In this post, we explore how to integrate Amazon Aurora MySQL-Compatible Edition with a generative AI model using Amazon Aurora Machine Learning. We walk […]

Amazon Aurora MySQL-Compatible Edition offers multiple authentication methods to securely authenticate database user access and meet different security needs. The most common method of authentication is using a user name and password. This can create additional overhead for both users and database administrators to manage and rotate these credentials; it also requires additional investments in […]

Amazon Aurora backs up cluster volumes automatically and retains restore data for the length of the backup retention period. Aurora automated backups are continuous and incremental, so you can restore to any point within the backup retention period from 1–35 days. If you need to retain backups for more than 35 days, you can take manual snapshots […]

At AWS, we have been making steady progress towards bringing our zero-ETL vision to life. With Amazon Aurora zero-ETL integration to Amazon Redshift, you can bring together the transactional data of Amazon Aurora with the analytics capabilities of Amazon Redshift. The integration helps you derive holistic insights across many applications, break data silos in your […]

In this post, we show you a recent improvement for Amazon RDS Blue/Green Deployment switchovers to reduce your overall downtime when you have a large number of connections to your database. Blue/Green Deployments enforce safety measures to make sure that the switchover from your blue environment to the green environment maintains data consistency. For reference, […]