Traditional logical data warehouses struggle with diverse data sources and poor physical computing. They often rely on SQL, which fails to handle NoSQL, JSON, and file systems effectively, while offering weak performance for large datasets. This creates a gap between logical flexibility and physical speed.

SPL, an open-source engine, addresses this by connecting directly to dozens of sources like NoSQL, CSV, and Kafka without forcing them into SQL tables. It performs cross-source mixed computation by leveraging each source's native syntax and capabilities, avoiding the limitations of pure SQL translation.

Beyond integration, SPL provides robust physical computing with high-performance algorithms and flexible file storage. This hybrid approach—combining logical integration with physical processing—enables faster queries and simpler development, reducing the need for complex, multi-tool technology stacks.