An Experimental Analysis of Using Different Storage Technologies in a Relational DBMS
Abstract
Traditional Database Management Systems (DBMS) are built on the premise that data is stored on hard disks drives (HDD). Recently, alternatives to HDDs have emerged, such as solid state drives (SSD), non-volatile memories (NVM) and new main memories (DRAM). Different characteristics of these devices may impact the performance of DBMSs. In this work, we propose to analyze a DBMS that stores its data in four different ways, in HDD, SSD NVM, DRAM and in a hybrid way, using the three devices together. To do this, we use a TPC-C workload and discuss the reasons that give rise to the results obtained for each type of storage.
Keywords:
DBMS, Storage, NVM, New Technologies
References
Brayner, A. and Monteiro, J. M. (2016). Hardware-aware database systems: A new era for database technology is coming - vision paper. In 31o Simpósio Brasileiro de Banco de Dados, SBBD 2016, Salvador, Bahia, Brasil, October 4-7, 2016., pages 187–192.
Difallah, D. E., Pavlo, A., Curino, C., and Cudre-Mauroux, P. (2013). Oltp-bench: An extensible testbed for benchmarking relational databases. Proc. VLDB Endow., 7(4):277- 288. DOI: https://doi.org/10.14778/2732240.2732246
Leo Kelion, BBC, I. M. (2015). 3d xpoint technology. https://www.bbc.com/ news/technology-33675734. Accessed: 2019-07-15.
Shah, M. A., Harizopoulos, S., Wiener, J. L., and Graefe, G. (2008). Fast scans and joins using flash drives. In 4th Workshop on Data Management on New Hardware, DaMoN 2008, Vancouver, BC, Canada, June 13, 2008, pages 17–24. DOI: https://doi.org/10.1145/1457150.1457154
Son, Y., Kang, H., Han, H., and Yeom, H. Y. (2016). An empirical evaluation and analysis of the performance of NVM express solid state drive. Cluster Computing, 19(3):1541–1553. DOI: https://doi.org/10.1007/s10586-016-0591-8
Xu, Q., Siyamwala, H., Ghosh, M., Suri, T., Awasthi, M., Guz, Z., Shayesteh, A., and Balakrishnan, V. (2015). Performance analysis of nvme ssds and their implication on real world databases. In Proceedings of the 8th ACM International Systems and Storage Conference, SYSTOR 2015, Haifa, Israel, May 26-28, 2015, pages 6:1–6:11. DOI: https://doi.org/10.1145/2757667.2757684
Zukowski, M. (2009). Balancing vectorized query execution with bandwidth-optimized storage. Journal of Computational Physics - J COMPUT PHYS.
Difallah, D. E., Pavlo, A., Curino, C., and Cudre-Mauroux, P. (2013). Oltp-bench: An extensible testbed for benchmarking relational databases. Proc. VLDB Endow., 7(4):277- 288. DOI: https://doi.org/10.14778/2732240.2732246
Leo Kelion, BBC, I. M. (2015). 3d xpoint technology. https://www.bbc.com/ news/technology-33675734. Accessed: 2019-07-15.
Shah, M. A., Harizopoulos, S., Wiener, J. L., and Graefe, G. (2008). Fast scans and joins using flash drives. In 4th Workshop on Data Management on New Hardware, DaMoN 2008, Vancouver, BC, Canada, June 13, 2008, pages 17–24. DOI: https://doi.org/10.1145/1457150.1457154
Son, Y., Kang, H., Han, H., and Yeom, H. Y. (2016). An empirical evaluation and analysis of the performance of NVM express solid state drive. Cluster Computing, 19(3):1541–1553. DOI: https://doi.org/10.1007/s10586-016-0591-8
Xu, Q., Siyamwala, H., Ghosh, M., Suri, T., Awasthi, M., Guz, Z., Shayesteh, A., and Balakrishnan, V. (2015). Performance analysis of nvme ssds and their implication on real world databases. In Proceedings of the 8th ACM International Systems and Storage Conference, SYSTOR 2015, Haifa, Israel, May 26-28, 2015, pages 6:1–6:11. DOI: https://doi.org/10.1145/2757667.2757684
Zukowski, M. (2009). Balancing vectorized query execution with bandwidth-optimized storage. Journal of Computational Physics - J COMPUT PHYS.
Published
2019-10-07
How to Cite
PRACIANO, Francisco D. B. S.; DE SOUSA, Joaquim Filipe L.; MACHADO, Javam C..
An Experimental Analysis of Using Different Storage Technologies in a Relational DBMS. In: BRAZILIAN SYMPOSIUM ON DATABASES (SBBD), 34. , 2019, Fortaleza.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 259-264.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2019.8833.
