Amazon Redshift extends SQL capabilities to simplify and speed up data warehouse migrations (preview)

Amazon Redshift now supports new SQL functionalities namely, MERGE, ROLLUP, CUBE, and GROUPING SETS, to simplify building multi-dimensional analytics applications and incorporating fast changing data in Redshift. In addition, Amazon Redshift now extends support for a larger, semi-structured data size (up to 16 MB) when ingesting nested data from JSON and PARQUET source files. Together, these enhancements reduce the code conversion effort if you are migrating to Amazon Redshift from other data warehouse systems and help improve performance.

For Amazon Redshift customers who are migrating from other data warehouse systems or who regularly need to ingest fast changing data into their Redshift warehouse, a single MERGE SQL command now offers an easier way to conditionally insert, update, and delete from target tables based on existing and new source data. If you need to perform multi-dimensional analysis, you can now simplify your applications by offloading the complex aggregation logic and run OLAP queries such as ROLLUP, CUBE, and GROUPING SETS as part of the SQL directly on the Amazon Redshift warehouse. With these new commands, you can avoid complex data processing code in your applications and also help improve your performance by running these analytics inside Amazon Redshift. With the larger, semi-structured data support extending from 1 MB to 16 MB, you can also simplify data ingestion pipelines involving large nested data by minimizing pre-processing on these files prior to loading into Redshift.

These new SQL capabilities that simplify and speed up data warehouse migrations in Amazon Redshift are available as a preview in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), Europe (Ireland), Europe (Stockholm).

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