Amazon Aurora with PostgreSQL compatibility is now available with machine learning capabilities, an option to export data into Amazon S3, and compatibility with updated PostgreSQL versions.
You can use Aurora to add machine learning (ML) based predictions to your applications, using a simple, optimized, and secure integration with Amazon SageMaker and Amazon Comprehend. Aurora machine learning is based on the familiar SQL programming language, so you don’t need to build custom integrations, move data around, learn separate tools, or have prior machine learning experience. This functionality is also available for Aurora with MySQL 5.7 compatibility.
Aurora machine learning supports any ML model available in SageMaker, or you can run sentiment analysis using Comprehend. It’s available for PostgreSQL 10 and 11, with no additional charge beyond the price of the AWS services that you are using. For more information, read the launch blog, the Aurora ML feature page, and the Aurora documentation.
