Scaling the Memory Power Wall with DRAM-Aware Data Management

Improving the energy efficiency of database systems has emerged as an important topic of research over the past few years. While significant attention has been paid to optimizing the power consumption of tradition disk-based databases, little attention has been paid to the growing cost of DRAM power consumption in main-memory databases (MMDB). In this paper, we bridge this divide by examining power– performance tradeoffs involved in designing MMDBs. In doing so, we first show how DRAM will soon emerge as the dominating source of power consumption in emerging MMDB servers unlike traditional database servers, where CPU power consumption overshadows that of DRAM. Second, we show that using DRAM frequency scaling and power-down modes can provide substantial improvement in performance/Watt under both transactional and analytical workloads. This, again contradicts rules of thumb established for traditional servers, where the most energy-efficient configuration is often the one with highest performance. Based on our observations, we argue that the long-overlooked task of optimizing DRAM power consumption should henceforth be considered a first-class citizen in designing MMDBs. In doing so, we highlight several promising research directions and identify key design challenges that must be overcome towards achieving this goal.