A workload-dependent performance analysis of an in-memory database in a multi-tenant configuration

Dominik Paluch, Harald Kienegger, Helmut Krcmar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Modern in-memory database systems begin to provide multi-tenancy features. In contrast to the traditional operation of one large database appliance per system, the utilization of the multi-tenancy features allows for multiple database containers running on one system. Consequently, the database tenants share the same system resources, which has an influence on their performance. Understanding the performance of database tenants in different setups with varying workloads is a challenging task. However, knowledge of the performance behavior is crucial in order to benefit from multi-tenancy. In this paper, we provide fine-grained performance insights of the in-memory database SAP HANA in a multi-tenant configuration. We perform multiple benchmark runs utilizing an online analytical processing benchmark in order to retrieve information about the performance behavior of the multi-tenant database containers. Furthermore, we provide an analysis of the collected results and show a more efficient usage of threads in an environment with less active tenants under specific workload conditions.

Original languageEnglish
Title of host publicationICPE 2018 - Companion of the 2018 ACM/SPEC International Conference on Performance Engineering
PublisherAssociation for Computing Machinery, Inc
Pages131-134
Number of pages4
ISBN (Electronic)9781450356299
DOIs
StatePublished - 2 Apr 2018
Event9th ACM/SPEC International Conference on Performance Engineering, ICPE 2018 - Berlin, Germany
Duration: 9 Apr 201813 Apr 2018

Publication series

NameICPE 2018 - Companion of the 2018 ACM/SPEC International Conference on Performance Engineering
Volume2018-January

Conference

Conference9th ACM/SPEC International Conference on Performance Engineering, ICPE 2018
Country/TerritoryGermany
CityBerlin
Period9/04/1813/04/18

Keywords

  • In-memory Database
  • Multi-Tenancy
  • Performance Analysis
  • SAP HANA

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