How can you choose the best database engine for Amazon Aurora?

1 Database engines explained

A database engine is the software component that manages the storage, retrieval, and manipulation of data in a database. Different database engines have different features, capabilities, and limitations that affect how they perform and interact with applications and users. For example, some database engines support more data types, functions, or extensions than others, or have different levels of compatibility with other database systems.

3 How to choose the best database engine for Amazon Aurora

When it comes to choosing the best database engine for Amazon Aurora, there is no one-size-fits-all answer. It depends on factors such as existing data, applications, skills, preferences, and objectives. To make an informed decision, consider whether you have data or applications that use MySQL or PostgreSQL and want to migrate them to Aurora with minimal changes. In that case, you may want to stick with the same database engine or use the compatible version to benefit from Aurora's performance and availability improvements. If you are starting from scratch or have the flexibility to choose a new database engine, compare the features and capabilities of MySQL and PostgreSQL and see which one meets your needs better. Additionally, if you have mixed requirements, test and benchmark different database engines on Aurora using sample data and queries. Lastly, take advantage of the AWS Schema Conversion Tool and the AWS Database Migration Service to convert and migrate your data and schema between different database engines.

4 Best practices and tips for using Amazon Aurora database engines

When using Amazon Aurora, it is important to follow some best practices and tips to optimize your experience and results. To begin, use the latest version and patch level of your database engine, as they may contain bug fixes, security updates, and performance enhancements. Additionally, use the recommended instance types and sizes for your database engine, as they may affect the performance, availability, and cost of your database cluster. Furthermore, use the appropriate parameter groups and settings for your database engine, as they may affect the behavior, functionality, and performance of your database cluster. It is also important to monitor and tune your database engine performance using metrics, alarms, logs, and events provided by AWS. Additionally, secure and protect your database engine data using encryption, authentication, authorization, and auditing features provided by AWS. Lastly, use the AWS Backup service to create and manage backups and restore points for your database cluster, as well as the AWS KMS service to manage encryption keys.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?