We present an overview of SAP HANA's Native Store Extension (NSE). This extension substantially increases database capacity, allowing to scale far beyond available system memory. NSE is based on a hybrid in-memory and paged column store architecture composed from data access primitives. These primitives enable the processing of hybrid columns using the same algorithms optimized for traditional HANA's in-memory columns. Using only three key primitives, we fabricated byte-compatible counterparts for complex memory resident data structures (e.g. dictionary and hash-index), compressed schemes (e.g. sparse and run-length encoding), and exotic data types (e.g. geo-spatial). We developed a new buffer cache which optimizes the management of paged resources by smart strategies sensitive to page type and access patterns. The buffer cache integrates with HANA's new execution engine that issues pipelined prefetch requests to improve disk access patterns. A novel load unit configuration, along with a unified persistence format, allows the hybrid column store to dynamically switch between in-memory and paged data access to balance performance and storage economy according to application demands while reducing Total Cost of Ownership (TCO). A new partitioning scheme supports load unit specification at table, partition, and column level. Finally, a new advisor recommends optimal load unit configurations. Our experiments illustrate the performance and memory footprint improvements on typical customer scenarios.

The EN50128 Railway Safety Standard recommends the use of formal methods for proving the correctness of the yard-specific logic, which was developed for electronic signaling and interlocking systems. We present a tool flow, which consists of three components. The core component uses a novel method for automatically generating the relevant safety properties for a yard from its control table. The second component proves the validity of the properties on the application logic by using a new theory of invariant checking. The third component leverages the suite of formal properties to prioritize site acceptance test points. Experimental results are presented on real application data for the yards in India that are demonstrating the performance of the proposed methods.