TY - GEN
T1 - A workload-dependent performance analysis of an in-memory database in a multi-tenant configuration
AU - Paluch, Dominik
AU - Kienegger, Harald
AU - Krcmar, Helmut
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/4/2
Y1 - 2018/4/2
N2 - 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.
AB - 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.
KW - In-memory Database
KW - Multi-Tenancy
KW - Performance Analysis
KW - SAP HANA
UR - http://www.scopus.com/inward/record.url?scp=85052015553&partnerID=8YFLogxK
U2 - 10.1145/3185768.3186290
DO - 10.1145/3185768.3186290
M3 - Conference contribution
AN - SCOPUS:85052015553
T3 - ICPE 2018 - Companion of the 2018 ACM/SPEC International Conference on Performance Engineering
SP - 131
EP - 134
BT - ICPE 2018 - Companion of the 2018 ACM/SPEC International Conference on Performance Engineering
PB - Association for Computing Machinery, Inc
T2 - 9th ACM/SPEC International Conference on Performance Engineering, ICPE 2018
Y2 - 9 April 2018 through 13 April 2018
ER -