Concepts
This page provides an overview of the core concepts of Dremio. For more details on the Dremio concepts and architecture, please refer to the official Dremio Architecture documentation.
Dremio is a data lakehouse platform designed to facilitate high-performance, self-service analytics directly on large datasets. By enabling direct querying of data stored in various formats across multiple sources, Dremio eliminates the need for complex ETL processes and data replication.
Key Concepts
Section titled “Key Concepts”The key concepts of Dremio, as outlined in their official Key Concepts documentation, focus on data organization, performance optimization, and user workspace management.
The different key concepts include:
Tables and Views
Section titled “Tables and Views”Primary data structures and logical representations of data.
Reflections
Section titled “Reflections”Precomputed, optimized copies of source data or query results. They are Dremio’s main feature to improve performance.
Spaces and Folders
Section titled “Spaces and Folders”Provide the organizational structure for managing data. Allowing users to group views by topics, like for project, department, or region.
Refer to the official Dremio documentation for more details about the key concepts listed above.