Amazon Aurora zero-ETL integration with Amazon Redshift enables near real-time analytics and machine learning (ML) using Amazon Redshift on petabytes of transactional data. Within seconds of transactional data being written into Amazon Aurora, zero-ETL seamlessly makes the data available in Amazon Redshift, eliminating the need to build and maintain complex data pipelines that perform extract, transform, and load (ETL) operations.


Near real-time data access

Access transactional data from Aurora in Amazon Redshift within seconds to run near real-time analytics and ML on petabytes of data.

Easy to use

Quickly analyze your transactional data in near real time without having to build and manage ETL pipelines to move transactional data to analytics systems.

Seamless data integration

Consolidate data from multiple Aurora database clusters and replicate your data to one Amazon Redshift data warehouse to run unified analytics across multiple applications and data sources.

No infrastructure management

Run near real-time analytics on transactional data without having to manage any infrastructure when using both Amazon Aurora Serverless v2 and Amazon Redshift Serverless.

Use cases

Near real-time operational analytics

Use Amazon Redshift analytics and ML capabilities to derive insights in near real time from transactional and other data to effectively respond to critical, time-sensitive events. Near real-time analytics can help you get more accurate and timely insights for use cases such as content targeting, optimized gaming experience, data quality monitoring, fraud detection, and customer behavior analysis.

Analytics at scale

With the Aurora zero-ETL integration with Amazon Redshift, you can use Amazon Redshift capabilities to analyze petabytes of your transactional data consolidated from multiple Aurora database clusters. You can take advantage of the comprehensive analytical capabilities of Amazon Redshift, such as built-in ML, materialized views, data sharing, and federated access to multiple data stores and data lakes. With Amazon Redshift ML, you can run billions of predictions with straightforward SQL commands with native integration into Amazon SageMaker.

Reduce operational burden

Moving data from a transactional database into a central data warehouse often requires building, maintaining, and operating a complex data pipeline ETL solution. With a zero-ETL integration, you can seamlessly replicate the schema, existing data, and data changes from your Aurora database to a new or existing Amazon Redshift cluster. Zero-ETL integration removes the need for complex data pipeline management.

How to Get Started

To create your zero-ETL integration between Aurora and Amazon Redshift, you specify an Aurora DB cluster as the data source and an Amazon Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. The data becomes available in Amazon Redshift within seconds, allowing data analysts to begin using Amazon Redshift analytics and ML functionality on the data. To learn more, please visit the getting started guides for Aurora and Amazon Redshift.


AWS does not charge an additional fee for Aurora zero-ETL integration with Amazon Redshift. You pay for existing Aurora and Amazon Redshift resources used to create and process the change data generated as part of a zero-ETL integration. These resources could include:
  • Additional I/O and storage used by enabling change data capture
  • Snapshot export costs for the initial data export to seed your Amazon Redshift databases
  • Additional Amazon Redshift storage for storing replicated data
  • Cross-AZ data transfer costs for moving data from source to target.

Ongoing processing of data changes is offered at no additional charge. For more information, please visit the Aurora pricing page

Learn more about the features of Amazon Aurora

Visit the features page