In this article, we are going to discuss how to set up a MySQL instance on AWS RDS using Cloud Formation templates. In my previous article, How to configure an Amazon RDS environment for MySQL, I have provided a detailed walkthrough of how to set up a MySQL instance on Amazon. You can use the AWS console to provide all the information required for setting up the instance and then use it. However, in this article, we will discuss an automated way of achieving the same functionalities using Cloud Formation templates.

In this article, we will explore the following topics:

• Amazon Aurora or Amazon RDS database snapshot export to S3 bucket
• Use AWS Glue to crawl the Snapshot and generate a data catalog
• Use Amazon Athena to query the data catalog
• Export Amazon Athena query results into S3 bucket

Amazon Aurora provides a MySQL and PostgreSQL compatible relation database with performance and feature enhancements over the existing databases. In the previous articles, we discussed the following features. You can refer to ToC at the bottom.

• Backtrack
• Global Database
• Amazon Aurora Serverless

In this article, we will cover fast database cloning and its usage for aurora databases.

In this 4^th article for the Amazon Aurora series, we will discuss and implement an Amazon Aurora Serverless cluster.

In this article, we will explore the useful backtrack feature for Amazon Aurora clusters.

In the article, Deploy your AWS RDS Aurora database clusters for MySQL, we explored the Amazon Aurora concept and deployment. In this article, we will understand about the global database feature and its implementations.

Introduction

Amazon offers managed database service for various database products such as Microsoft SQL Server, MySQL, PostgreSQL, Oracle. In these relational database services (RDS), AWS manages the operating system, networking components, backups, monitoring solutions. In the previous articles, we explored many useful RDS features under the AWS RDS category on SQLShack.