dbt and Amazon Redshift Data Sharing: Multi-cluster pipelines without moving a byte

This article demonstrates how to use Amazon Redshift Data Sharing with dbt Cloud to build multi-cluster analytics pipelines without copying data between clusters.

• Amazon Redshift Data Sharing enables secure, live data sharing across clusters and accounts without data movement
• dbt Cloud manages data transformations with software engineering best practices like CI/CD and documentation
• Datashares work at the namespace level, granting read-only access to producer data on consumer clusters
• Enable datasharing: true in dbt profiles to access shared objects via cross-database system views
• Use table materialization for models reading datashare sources; views cannot reference shared objects
• Step-by-step setup includes creating datashares, granting access, building dbt models, and deploying transformations

This architecture delivers transactionally consistent live data access, eliminates duplicate storage, and maintains unified governance across producer and consumer clusters.