Amazon Redshift Serverless feature overview - Amazon Redshift

Amazon Redshift Serverless feature overview

Most of the features supported by an Amazon Redshift provisioned data warehouse are also supported by Amazon Redshift Serverless. The following are some of its key capabilities.

Feature Description

Snapshots

You can restore a snapshot of Amazon Redshift Serverless or a provisioned data warehouse to Amazon Redshift Serverless. For more information, see Working with snapshots and recovery points.

Recovery points

Amazon Redshift Serverless automatically creates a point of recovery every 30 minutes. These recovery points are kept for 24 hours. You can use them to restore after accidental writes or deletes. When you restore from a recovery point, all the data in your Amazon Redshift Serverless database is restored to an earlier point in time. You can also create a snapshot from a recovery point if you need to keep a point of recovery for a longer period. For more information, see Working with snapshots and recovery points.

Base RPU capacity

You can set a base capacity in Redshift Processing Units (RPUs). One RPU provides 16 GB of memory. This setting gives you the ability to control the balance between resources in use and cost for your workload. You can increase this value to grow resources available and improve query performance, or lower the value to limit your spending. The default is 128 RPUs. You can also set usage limits, such as RPUs used per day, to control costs. For more information, see Billing for Amazon Redshift Serverless.

Usage limits of data sharing

You can limit the amount of data transferred from a producer Region to a consumer Region using the console or the API. These data transfer costs differ by AWS Region, and are measured in terabytes. For more information about data sharing, see Getting started data sharing using the console in the Amazon Redshift Database Developer Guide.

User-defined functions (UDFs)

You can run user-defined functions (UDFs) in Amazon Redshift Serverless. For more information, see Creating user-defined functions in the Amazon Redshift Database Developer Guide.

Stored procedures

You can run stored procedures in Amazon Redshift Serverless. For more information, see Creating stored procedures in the Amazon Redshift Database Developer Guide.

Materialized views

You can create materialized views in Amazon Redshift Serverless. For more information, see Creating materialized views in the Amazon Redshift Database Developer Guide.

Spatial functions

You can run spatial functions in Amazon Redshift Serverless. For more information, see Querying spatial data in the Amazon Redshift Database Developer Guide.

Federated queries

You can run queries to join data with Aurora DB cluster and Amazon RDS databases from Amazon Redshift Serverless. For more information, see Querying data with federated queries in the Amazon Redshift Database Developer Guide.

Data lake queries

You can run queries to join data from your Amazon S3 data lake with Amazon Redshift Serverless. For more information, see Querying a data lake in the Amazon Redshift Management Guide.

HyperLogLog

You can run HyperLogLog functions in Amazon Redshift Serverless. For more information, see Using HyperLogLog sketches in the Amazon Redshift Database Developer Guide.

Querying data across databases

You can query data across databases with Amazon Redshift Serverless. For more information, see Querying data across databases in the Amazon Redshift Database Developer Guide.

Data sharing

You can access datashares on provisioned data warehouses with Amazon Redshift Serverless. For more information, see Sharing data across clusters in the Amazon Redshift Database Developer Guide.

Semistructured data querying

You can ingest and store semistructured data with the SUPER data type with Amazon Redshift Serverless. For more information, see Ingesting and querying semistructured data in the Amazon Redshift Database Developer Guide.

Tagging resources

You can use the AWS CLI or the Amazon Redshift Serverless API to tag resources with metadata related to the resource. For more information, see Tagging resources.

Machine learning

You can use Amazon Redshift machine learning with Amazon Redshift Serverless. For more information, see Using machine learning in the Amazon Redshift Database Developer Guide.

SQL commands and functions

With a few exceptions (such as REBOOT_CLUSTER), you can use Amazon Redshift SQL commands and functions with Amazon Redshift Serverless. For more information, see SQL reference in the Amazon Redshift Database Developer Guide.

CloudFormation resources

Using CloudFormation templates, you can deploy and update Amazon Redshift Serverless resources. This integration means you can spend less time managing resources and focus on your applications. For more information about CloudFormation resources in Amazon Redshift Serverless, see Amazon Redshift Serverless resource type reference.

CloudTrail resources

Amazon Redshift Serverless is integrated with AWS CloudTrail to provide a record of actions taken in Amazon Redshift Serverless. CloudTrail captures all API calls for Amazon Redshift Serverless as events. For more information, see CloudTrail for Amazon Redshift Serverless.