Difference between Amazon Aurora and Amazon RDS?
Databases are incredibly important for applications. They are also essential for smoother operations of the business. As a database administrator or DBA, you are under constant stress to make sure that the applications perform well with minimal downtime while having to face numerous challenges.
Increasingly complex databases and growing workloads are the major challenges that a DBA often faces. Thanks to the preference for shifting to application-focused processes and the introduction of multiple platforms for databases, there is a growing demand for managing data on-site and on the cloud.
In this article, we have outlined every essential USP and highlighted factors for two of the world’s most popular relational databases offered by Amazon Web Service (AWS), so you can know the difference between Amazon Aurora and Amazon RDS.
What is Amazon Aurora?
Amazon Aurora is a relational database engine. It combines the speed and reliability of expensive, high-end commercial databases with the affordability and simplicity of open-source databases. Amazon Aurora is compatible with MySQL but performs at least 5 times faster than standard MySQL.
Aurora is designed to help DBAs save time and effort otherwise spent in planning backup storage disks by automating the task but without affecting the performance of the end-user. This makes backing up windows and automating backup scripts completely redundant.
Aurora works to replicate data into six storage nodes in multiple Availability Zones to cushion the loss of an entire Availability Zone. It can also use two storage nodes simultaneously without affecting the client’s applications.
What is Amazon RDS?
Amazon RDS (Relational Database Service) is designed to ease the process of setting up, operating and scaling a relational database in the cloud. It is an affordable and scalable (resizable) capacity that automatically manages otherwise time-consuming administrative tasks which gives DBAs the freedom to focus on core aspects.
Amazon RDS is offered through six popular database engines, including Amazon Aurora, MySQL, PostgreSQL, Oracle, Microsoft SQL Server and MariaDB.
Main differences between Amazon Aurora and Amazon RDS
Now that you know the basic functions of the two, let’s take a closer look at the distinctive features that show you the difference between Amazon Aurora and RDS:
Businesses focus intensely on performance and DBAs have to ensure high-performance throughput with the available hardware.
Performance of Amazon Aurora
Amazon Aurora offers 5 times faster throughput than MySQL and 3 times faster throughput as compared to PostgreSQL, running on the same hardware. Amazon uses unique hardware and software techniques that ensure that the database engine can completely utilize the existing computing, storage and networking capacities.
Performance of Amazon RDS
Amazon RDS offers users a choice between two SSD-backed storage features. One of these is optimized for high-end OTLP applications while the other storage feature is designed for regular, affordable use.
The first option provides a storage type that is optimized for I/O intensive transactional (OTLP) database workloads and lets users provision as many as 30,000 IOPS per database instance.
The second SSD-backed storage feature is offered as a cost-effective, general-purpose storage option that can deliver a constant baseline of at least 3 IOPS per GB of provisioned storage space.
Compatibility with Database Engines
For moving your conventional on-site database to the cloud, or from RDS to Aurora, DBAs need to meet their SLAs. Every step needs to be performed with minimal or no downtime.
Compatibility of Amazon Aurora
Amazon Aurora is compatible with MySQL and PostgreSQL. If you use MySQL software or PostgreSQL for your database, then Aurora is highly recommended for you because it works perfectly well with MySQL 5.6 and PostgreSQL 9.6.1. This enables the existing database and application tools to keep running on Aurora without the need to be modified.
Compatibility of Amazon RDS
You can easily shift your database from on-site or EC2-hosted databases, such as SQL Server, Oracle or PostgreSQL to Amazon RDS in a simple, efficient way using AWS Database Migration Service.
Storage auto-scaling is extremely important in today’s day and age when databases continue to grow at a constant speed.
Storage Auto-Scaling of Amazon Aurora
Depending on the use of the database, Amazon Aurora is designed to grow, from a minimum of 10 GB all the way up to 64 TB, in increments of 10 GB, but without affecting the performance of the database. Amazon Aurora does not require DBAs to provision capacity beforehand. This way, Amazon Aurora helps DBAs to avoid wasting time in forecasting and specifying storage allocation and ensure smooth and fast business operations. However, Aurora only supports the InnoDB storage engine and tables from other storage engines are automatically transformed into InnoDB.
Storage Auto-Scaling of Amazon RDS
Amazon RDS requires users to allow at least 6 TB of storage space on the go with no downtime.
After going through the major differences between the two, it is safe to say that Amazon Aurora is designed for DBAs who are looking for SQL compatibility and auto-scaling. On the other hand, Amazon RDS is meant for DBAs who need SSD-backed storage options for faster application processing.