Amazon Redshift

Amazon Redshift is a cloud data warehouse designed to process large amounts of data for analytics.

Launched in 2012, Redshift is a column-oriented relational database under the hood and natively supports SQL queries. As part of the AWS data analytics architecture, Redshift can load data from data lakes such as Amazon S3, other data warehouses, operational databases, and third party datasets. In addition, Redshift integrates some ML capabilities and works with Amazon SageMaker to train ML models.

Competitor data warehouses to Redshift include Snowflake, Google BigQuery, and Azure Synapse Analytics. Some data warehouse users believe that Redshift is less flexible than other solutions due to limitations in architecture and storage sizes.

Using Redshift Serverless

The original version of Amazon Redshift allows administrators to create provisioned server clusters. The Serverless option of Redshift became available in 2022 and is able to automatically adjust server capacity while reducing the need to manage clusters directly. In addition, Redshift Serverless only charges fees based on usage.

Note: Serverless solutions can have the cold start problem. This means that it can take longer for serverless solutions to respond to queries from an inactive state. Since a data warehouse such as Redshift is usually intended for internal analytics usage (and not end-customer usage), it still tends to be beneficial to use Redshift Serverless over the Redshift provisioned clusters option.

Creating a namespace and workgroup

If you haven’t used Redshift Serverless before, the Redshift area in the AWS Console displays a button that says “Try Redshift Serverless free trial.” Click this button.