Dynamic Filtering: Supporting High Speed Access to Data

Starburst Enterprise enhances data analytics performance across complex environments by utilizing dynamic filtering, particularly beneficial for data federation scenarios where data spans multiple sources such as data lakes and traditional warehouses. This feature, enabled by default, works by minimizing data transfer during query execution, thereby boosting performance and reducing network traffic and load on remote sources. In scenarios like financial services, retail, and banking, where quick data access is crucial, dynamic filtering optimizes query execution by loading smaller tables into memory and selectively fetching rows from larger tables, akin to an inner join but applicable across diverse data sources. This approach is part of a broader strategy that includes high-speed connectors and an MPP execution engine, allowing for efficient data analysis even in multi-cloud or hybrid environments.