Database systems on virtual machines: How much do you lose?

Umar Farooq Minhas, Jitendra Yadav, Ashraf Aboulnaga, Kenneth Salem

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Citations (Scopus)

Abstract

Virtual machine technologies offer simple and practical mechanisms to address many manageability problems in database systems. For example, these technologies allow for server consolidation, easier deployment, and more flexible provisioning. Therefore, database systems are increasingly being run on virtual machines. This offers many opportunities for researchers in self-managing database systems, but it is also important to understand the cost of virtualisation. In this paper, we present an experimental study of the overhead of running a database workload on a virtual machine. We show that the average overhead is less than 10%, and we present details of the different causes of this overhead. Our study shows that the manageability benefits of virtualisation come at an acceptable cost.

Original languageEnglish
Title of host publicationProceedings of the 2008 - IEEE 24th International Conference on Data Engineering Workshop, ICDE'08
Pages35-41
Number of pages7
DOIs
Publication statusPublished - 1 Sep 2008
Event2008 - IEEE 24th International Conference on Data Engineering Workshop, ICDE'08 - Cancun, Mexico
Duration: 7 Apr 200812 Apr 2008

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Other

Other2008 - IEEE 24th International Conference on Data Engineering Workshop, ICDE'08
CountryMexico
CityCancun
Period7/4/0812/4/08

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

Fingerprint Dive into the research topics of 'Database systems on virtual machines: How much do you lose?'. Together they form a unique fingerprint.

  • Cite this

    Minhas, U. F., Yadav, J., Aboulnaga, A., & Salem, K. (2008). Database systems on virtual machines: How much do you lose? In Proceedings of the 2008 - IEEE 24th International Conference on Data Engineering Workshop, ICDE'08 (pp. 35-41). [4498282] (Proceedings - International Conference on Data Engineering). https://doi.org/10.1109/ICDEW.2008.4498282