MonetDB/X100: Hyper-Pipelining Query Execution

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.