StagedDB: Designing Database Servers for Modern Hardware Stavros Harizopoulos and Anastassia Ailamaki   View Paper (PDF)   Return to June 2005, Databases for New Hardware, Volume 28, Number 2 Abstract Advances in computer architecture research yield increasingly powerful processors which can execute code at a much faster pace than they can access data in the memory hierarchy. Database management systems (DBMS), due to their intensive data processing nature, are in the front line of commercial applications which cannot harness the available computing power. To prevent the CPU from idling, a multitude of hardware mechanisms and software optimizations have been proposed. Their effectiveness, however, is limited by the sheer volume of data accessed and by the unpredictable sequence of memory requests. In this article we describe StagedDB, a new DBMS software architecture for optimizing data and instruction locality at all levels of the memory hierarchy. The key idea is to break database request execution in stages and process a group of sub-requests at each stage, thus effortlessly exploiting data and work commonality. We present two systems based on the StagedDB design. STEPS, a transaction coordinating mechanism demonstrated on top of Shore, minimizes instruction-cache misses without increasing the cache size, eliminating two thirds of all instruction misses when running on-line transaction processing applications. QPipe, a staged relational query engine built on top of BerkeleyDB, maximizes data and work sharing across concurrent queries, providing up to 2x throughput speedup in a decision-support workload. ©2006 Association for Computing Machinery