The Dremio Blog

Clustering is a data layout strategy that organizes rows based on the values of one or more columns, without physically splitting the dataset into separate partitions. Instead of creating distinct directory structures, like traditional partitioning does, clustering sorts and groups related rows together within the existing storage layout.

Integrating row column access control with materializations enables Dremio Reflections to deliver high-performance query execution without compromising on security or flexibility, making it an ideal solution for scalable, secure data access in the lakehouse architecture. Furthermore, by enabling pre-compute materializations to be re-usable across users and roles, significant cost savings can be achieved through more efficient engine resource utilization.

At Dremio, we implemented Autonomous Reflections in our own internal Data Lakehouse. We are happy to report that Autonomous Reflections exceeded our expectations. In just days, we saw significant improvements

Credential vending support in Dremio opens up a more secure and convenient way to query external Iceberg catalogs. By obtaining temporary, table-scoped credentials on the fly, Dremio minimizes long-lived secrets and ensures access is tightly controlled by the catalog’s policies.