Evaluating the Energy Efficiency of OLTP Operations

A Case Study on PostgreSQL
  • Raik Niemann
  • Nikolaos Korfiatis
  • Roberto Zicari
  • Richard Göbel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8127)

Abstract

With the continuous increase of online services as well as energy costs, energy consumption becomes a significant cost factor for the evaluation of data center operations. A significant contributor to that is the performance of database servers which are found to constitute the backbone of online services. From a software approach, while a set of novel data management technologies appear in the market e.g. key-value based or in-memory databases, classic relational database management systems (RDBMS) are still widely used. In addition from a hardware perspective, the majority of database servers is still using standard magnetic hard drives (HDDs) instead of solid state drives (SSDs) due to lower cost of storage per gigabyte, disregarding the performance boost that might be given due to high cost.

In this study we focus on a software based assessment of the energy consumption of a database server by running three different and complete database workloads namely TCP-H, Star Schema Benchmark -SSB as well a modified benchmark we have derived for this study called W22. We profile the energy distribution among the most important server components and by using different resource allocation we assess the energy consumption of a typical open source RDBMS (PostgreSQL) on a standard server in relation with its performance (measured by query time).

Results confirm the well-known fact that even for complete workloads, optimization of the RDBMS results to lower energy consumption.

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Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Raik Niemann
    • 1
    • 2
  • Nikolaos Korfiatis
    • 2
  • Roberto Zicari
    • 2
  • Richard Göbel
    • 1
  1. 1.Institute of Information SystemsUniversity of Applied Science HofHofGermany
  2. 2.Database and Information Systems, Institute for Informatics and MathematicsGoethe University FrankfurtFrankfurt am MainGermany

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