Amazon Redshift now supports multi-data warehouse writes through data sharing (preview)
Amazon Redshift now supports multi-data warehouse writes through data sharing in public preview. You can start writing to Redshift databases from multiple Redshift data warehouses in just a few clicks. The written data is available to all warehouses as soon as it is committed. This allows teams to flexibly scale compute by adding warehouses of different types and sizes based on their write workloads’ price-performance needs, isolate compute to more easily meet SLAs, and easily and securely collaborate with other teams.
Amazon Redshift now supports multi-data warehouse writes through data sharing in public preview. You can start writing to Redshift databases from multiple Redshift data warehouses in just a few clicks. The written data is available to all warehouses as soon as it is committed. This allows teams to flexibly scale compute by adding warehouses of different types and sizes based on their write workloads’ price-performance needs, isolate compute to more easily meet SLAs, and easily and securely collaborate with other teams.
With multi-data warehouse writes through data sharing, you can easily keep ETL jobs more predictable by splitting workloads between multiple warehouses, helping you meet your SLAs with less time and effort. You can track usage and control costs as each team or application can write using its own warehouse, regardless of where the data is stored. You can use warehouses of different types (clusters and serverless workgroups) and sizes so that you can tune your warehouse for your workloads’ price-performance needs. Teams can also easily collaborate as written data is immediately available to all warehouses as soon as it is committed, even when written across accounts and regions.
Amazon Redshift’s support for multi-warehouse writes through data sharing is available on ra3.4xl clusters, ra3.16xl clusters, and serverless workgroups using the PREVIEW_2023 track in all regions the track is available. Preview features are provided primarily for evaluation and testing and should not be used in production systems. For preview terms and conditions, see Beta Service Participation in AWS Service Terms.