Amazon Aurora vs. Amazon RDS vs. Amazon Redshift – Key Differences You Should Know About

Santosh Karla | 4 min read

Data management is a highly time-consuming task for most companies, while it shouldn’t be. Today, several ‘Storage On-demand’ service providers offer managed cloud-based services by catering to your infrastructure requirements, managing backups, patching software, and automating general administrative tasks.

Amazon Web Services (AWS), one of the leading cloud service providers, offers a wide range of database solutions, the three most popular being Amazon Aurora, Redshift, and RDS. While all three are database solutions, they are indeed very different from each other. As a result, deciding which one is best for your company’s needs may be difficult.

This article provides an overview of each of them to help you decide on your database solutions.

Amazon RDS

Amazon RDS service is a managed, easy-to-setup, and scale relational database service. It is your first point of call for database service if you are unloading your database management workload.

As it is popularly known, RDS is a comprehensive managed SQL database service that’s compatible with the six most popular database engines, including Amazon Aurora, MariaDB, MySQL, PostgreSQL, Microsoft SQL Server, and Oracle.

You can continue to use the applications and tools with your current database with RDS, and it is the only database service that is compatible with Microsoft SQL Server.


Amazon Redshift is also a managed relational database service. However, it differs from other DB solutions in managing vast volumes of data and processing structured and unstructured data.

It is specially designed to set up storage and analyze large-scale data as a data warehouse and perform database migrations on a large scale.

Redshift runs on its engine based on PostgreSQL, and it is robust in performance but might be a bit more complex than usual.

Redshift is an online analytical processing database specially designed to process complex analytical queries and calculations.

As already mentioned, Amazon Redshift is sometimes also referred to as a data warehouse to store large amounts of data and various functionalities. Hence, it is opted by large corporations for seamless management.

Amazon Aurora

Amazon Aurora is a fully managed relational database engine compatible with MySQL and PostgreSQL.

Amazon Aurora is a comprehensive managed relational database engine compatible with MySQL and PostgreSQL and runs on RDS or Aurora serverless.

Aurora contains an extremely high-performance storage subsystem, and its compatible MySQL and PostgreSQL database engines take advantage of the fast distributed storage.

Furthermore, Aurora is an enterprise solution and has better performance statistics compared to MySQL and PostgreSQL. It can deliver as much as five times the output of MySQL and three times more than PostgreSQL without any changes to your current applications



Comparatively, RDS is easy to scale because it is less complex. You can determine the auto scale max capacity by operating through the AWS console and running it on-demand or using a reserve capacity.

Redshift –

When it comes to scalability, there might be more downtime when scaling with Redshift due to complex infrastructure. Though you can scale it quickly using an Elastic resize, it still doesn’t match up to RDS.

However, RDS with its concurrent scaling feature can be preferred because it lets it take on unlimited queries.

Aurora –

The scaling capacity of Aurora depends on where it is running, whether it is RDS or Aurora Serverless. Aurora starts up automatically and scales up and down, and shuts down the line based on your applications.

However, Aurora isn’t the most robust solution and has its restrictions and limits for scaling.

To conclude, if your scaling needs are standard, then RDS is the best option. For more significant enterprise needs, you should most probably look at Redshift based on your budget, time, and the number of queries you will be running.

Aurora is the better option if you are looking for a powerful relational DB for non-analytical purposes. However, it would help if you considered the previously mentioned restrictions that come with Aurora serverless. Your choice ultimately depends on what you need to scale.



The engine determines the storage limit for RDS it is running on; Amazon Aurora has a limit of 64TB, SQL has a limit of 16TB, and all other engines have a limit of 32TB.

Redshift –

The maximum capacity for Redshift is much higher, as much as 2PB.

Aurora –

As mentioned earlier, when run on RDS, the maximum capacity for Aurora is up to 64TB.

Here Redshift is a clear winner for the most preferred choice when it comes to storage.

Pricing and Availability


RDS is comparatively more economical than others, but still, the pricing depends on which engine you use. They offer a pay-as-you-go model with two other options: a higher tariff option or a lower tariff reserved instance model with a limit to a certain amount of usage.

Redshift –

Redshift is an on-demand model, but RDS is also available on a reserved instance model. Due to the additional concurrency scaling feature, the pricing may vary.

Aurora –

Aurora, when run under RDS, the pricing falls under it. Still, with serverless, you are charged per Aurora capacity unit, commonly known as ACUs, which amounts to a memory of 2GB, and related compute and network.

So, in a nutshell, Redshift is comparatively more expensive due to its additional features affecting its pricing model.



AWS keeps your RDS instances primarily up to date, with the option for users to postpone specific updates.

Redshift –

While Redshift is easier to maintain than other traditional databases, it does necessitate more maintenance.

Aurora –

Again, the maintenance of Aurora is correspondent to RDS when run on RDS.

When it comes to maintenance, due to the complexity of Redshift, it is costlier to maintain. In contrast, Aurora and RDS can run with little or virtually no maintenance at all.

In conclusion, if you are looking to cut down on the management cost of a simple relational database service, then RDS is your best option.

But suppose you have sufficient budget, time, and resources to invest in a database service that handles and manages a considerable workload and complex queries and calculations. In that case, Redshift is your best bet.

AWS Aurora is best suited for enterprise-level applications with serverless options.

Your choice for the database depends on your business needs and system requirements, though most organizations use several databases. We hope this article will provide you with knowledge and insights to make an informed decision when selecting the database solution for your business.

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