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ABSTRACTCarnegie Mellon, School of Computer ScienceDBMbench: Microbenchmarking Database Systems in a Small, yet Real World Minglong Shao, Anastassia Ailamaki Carnegie Mellon University Database benchmarks are widely used to test functionality and evaluate the overall performance of database systems. However, the complexity involved in establishing the experimental environment and in conducting detailed analysis makes conventional benchmarks inappropriate for use in research that evaluates low-level hardware, such as processor microarchitecture and memory hierarchy performance behavior of database systems. In this paper, we first present a comprehensive performance study of the dominant DSS and OLTP benchmarks, and highlight their key processor and memory performance characteristics. We then introduce a systematic scaling framework to scale down conventional benchmarks and present extrapolation rules to predict the processor and memory behavior of full-scale benchmarks. Finally, we propose the DBMbench consisting of two substantially scaled-down microbenchmarks, MTPC-H and MTPC-C that accurately (> 95%) capture the processor and memory performance behavior of DSS and OLTP workloads. FULL PAPER: pdf |