In-Memory Database Query Energy Estimation: Modeling & Green Strategy Support

The miniaturization of electronic components, coupled with falling acquisition prices and increasing capacities, has led to the availability of many types of main memory data storage systems called In-Memory databases. Despite their inability to handle large volumes of data in memory, these systems offer considerable performance in query processing. This is due to the latency optimization of loading data from secondary memory. Nevertheless, their operation requires an execrable use of the main memory and also high energy consumption. With the torch of environmental sustainability being waved and the exorbitant energy cost, the development and application of energy reduction techniques within these systems is more urgent than ever. In this paper, we model the cost of energy consumption during query plan execution in an In-Memory database to develop energy-efficient approaches for query processing and benchmark tool designing.