Database systems tend to achieve only low IPC (instructions-per-cycle) efficiency on modern CPUs in compute-intensive application areas like decision support, OLAP and multimedia retrieval. This paper starts with an in-depth investigation to the reason why this happens, focusing on the TPC-H benchmark. Our analysis of various relational systems and MonetDB leads us to a new set of guidelines for designing a query processor. The second part of the paper describes the architecture of our new X100 query engine for the MonetDB system, that follows these guidelines. On the surface, it resembles a classical Volcano-style engine, but the crucial difference to base all execution on the concept of vector processing makes it highly CPU efficient. We evaluate the power of MonetDB/X100 on the 100GB version of TPC-H, showing its raw execution power to be between one and two orders of magnitude higher than previous technology.

Additional Metadata
THEME Information (theme 2)
Publisher Very Large Data Base Endowment
Conference Biennial Conference on Innovative Data Systems Research
Citation
Boncz, P.A, Zukowski, M, & Nes, N.J. (2005). MonetDB/X100: Hyper-Pipelining Query Execution. In Proceedings of International conference on verly large data bases (VLDB) 2005. Very Large Data Base Endowment.