And the user may choose to run DynamoDB on on-demand or in provisioned capacity mode, in which a limit can be set on scale, much like RDS.Īurora – How Aurora scales depends on whether it’s running on RDS or Aurora Serverless. At the extreme end of things, however, Redshift is probably the better choice, since its Concurrency Scaling feature – which costs extra – allows it to take on a virtually limitless amount of queries.ĭynamoDB – DynamoDB scales seamlessly with no impact on performance. Using Elastic Resize, Redshift can be scaled more quickly, but it still doesn’t quite close the gap with RDS. Redshift – Redshift’s infrastructure is more complicated, meaning there’ll be more downtime and complexity involved in scaling. It can be run using a reserved capacity or on-demand. RDS – Because RDS is less complex, it’s easier to scale – requiring just a few clicks on the AWS Console to determine an auto-scale max capacity. Aurora is MySQL and PostgreSQL compatible which means that the language which programs it is functionally similar to these engines, although it is an engine in its own right.įurther, Aurora has significantly higher performance stats compared to MySQL and PostgreSQL run on RDS.Īurora is also an enterprise solution, even when used with RDS. Amazon AuroraĪmazon Aurora is a database engine that can be run on RDS or as Aurora Serverless.
Key-value databases are best suited to certain use cases such as session data and shopping cart information and can achieve a fast throughput of read/write requests.ĭynamoDB is also an enterprise-level solution. This makes the data stored in DynamoDB ‘dynamic’ which means it’s easier to modify. DynamoDBĭynamoDB is a key-value database that runs the NoSQL engine, this means it treats all data within it as being composed of a list of attributes and values as opposed to data points constituted by the relationships between cells and column/row headers (as in a relational database). Redshift is an enterprise-level DB, mostly used by large companies. This means it’s especially suited to processing analyticalqueries involving more complex calculations.Because of its vast storage potential and differing functionality, Redshift is sometimes referred to as a data warehouse. Redshift is an OLAP database, standing for ‘online analytical processing’. See Also Amazon Redshift Vs DynamoDB - The Complete Comparison
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