An Experimental Analysis of the Use of Different Storage Technologies on a Relational DBMS
DOI:
https://doi.org/10.5753/jidm.2020.1868Keywords:
databases, storage technologies, hybrid storage, performance evaluationAbstract
Traditional Database Management Systems (DBMSs) are built with the premise that magnetic disks such as hard disks drives (HDDs) store the data. Recently, several alternatives to HDDs have emerged, such as the solid-state drives (SSDs) based on non-volatile memory (NVM) technology such as 3D XPoint and the new generations of dynamic random access memories (DRAMs). Different characteristics of these storage technologies may impact the performance of DBMSs. In this work, we analyze the performance of a DBMS using three storage technologies as data locations:HDD, SSD NVM, and DRAM, as well as a hybrid way combining all three. To do this, we use two workloads, analytical and transactional, and we observe throughput as well as latency. After, we discuss the reasons for the results obtained for each type of storage. We also show that the query processing can benefit from the different characteristics of each storage technology to perform faster queries and, finally, we analyze the benefits of using a hybrid storage system.
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Barata, M., Bernardino, J., and Furtado, P. An overview of decision support benchmarks: Tpc-ds, TPC-H and SSB. In New Contributions in Information Systems and Technologies - Volume 1 [WorldCIST’15, Azores, Portugal, April 1-3, 2015], Á. Rocha, A. M. R. Correia, S. Costanzo, and L. P. Reis (Eds.). Advances in Intelligent Systems and Computing, vol. 353. Springer, Portugal, pp. 619–628, 2015.
Brayner, A. and Monteiro, J. M. 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, Brazil, October 4-7, 2016, J. C. Machado (Ed.). SBC, Brazil, pp. 187–192, 2016.
Chaudhuri, S. and Dayal, U. An overview of data warehousing and olap technology. SIGMOD Rec. 26 (1): 65–74, Mar., 1997.
Chen, Y., Raab, F., and Katz, R. H. From TPC-C to big data benchmarks: A functional workload model. In Specifying Big Data Benchmarks - First Workshop, WBDB 2012, San Jose, CA, USA, May 8-9, 2012, and Second Workshop, WBDB 2012, Pune, India, December 17-18, 2012, Revised Selected Papers, T. Rabl, M. Poess, C. K. Baru, and H. Jacobsen (Eds.). Lecture Notes in Computer Science, vol. 8163. Springer, India, pp. 28–43, 2012.
Didona, D., Ioannou, N., Stoica, R., and Kourtis, K. Toward a better understanding and evaluation of tree structures on flash ssds. CoRR vol. abs/2006.04658, pp. 1–15, 2020.
Difallah, D. E., Pavlo, A., Curino, C., and Cudre-Mauroux, P. Oltp-bench: An extensible testbed for benchmarking relational databases. Proc. VLDB Endow. 7 (4): 277–288, Dec., 2013.
Eisenman, A., Gardner, D., AbdelRahman, I., Axboe, J., Dong, S., Hazelwood, K., Petersen, C., Cidon, A., and Katti, S. Reducing dram footprint with nvm in facebook. In Proceedings of the Thirteenth EuroSys Conference. EuroSys ’18. Association for Computing Machinery, New York, NY, USA, 2018.
Hady, F. T., Foong, A. P., Veal, B., and Williams, D. Platform storage performance with 3d xpoint technology. Proceedings of the IEEE 105 (9): 1822–1833, 2017.
Höppner, B., Waizy, A., and Rauhe, H. An approach for hybrid-memory scaling columnar in-memory databases. In International Workshop on Accelerating Data Management Systems Using Modern Processor and Storage Architectures - ADMS 2014, Hangzhou, China, September 1, 2014, R. Bordawekar, T. Lahiri, B. Gedik, and C. A. Lang (Eds.). VLDB Endowment, China, pp. 64–73, 2014.
Kelion, L., BBC, Intel, and Micron. 3d xpoint technology. https://www.bbc.com/news/technology-33675734, 2015. Accessed: 2019-07-15.
Kourtis, K., Ioannou, N., and Koltsidas, I. Reaping the performance of fast NVM storage with udepot. In 17th USENIX Conference on File and Storage Technologies, FAST 2019, Boston, MA, February 25-28, 2019, A. Merchant and H. Weatherspoon (Eds.). USENIX Association, USA, pp. 1–15, 2019.
Kuo, T.-W., Huang, P.-C., Chang, Y.-H., Ko, C.-L., and Hsueh, C.-W. An efficient fault detection algorithm for nand flash memory. SIGAPP Appl. Comput. Rev. 11 (2): 8–16, Mar., 2011.
Lepers, B., Balmau, O., Gupta, K., and Zwaenepoel, W. Kvell: the design and implementation of a fast persistent key-value store. In Proceedings of the 27th ACM Symposium on Operating Systems Principles, SOSP 2019, Huntsville, ON, Canada, October 27-30, 2019, T. Brecht and C. Williamson (Eds.). ACM, Canada, pp. 447–461, 2019.
Liu, X. and Salem, K. Hybrid storage management for database systems. Proc. VLDB Endow. 6 (8): 541–552, June, 2013.
McCallum, J. C. Memory prices (1957-2017). https://jcmit.net/memoryprice.htm, 2017. Accessed: 2020-10-28.
Mironov, V., Chernykh, I. G., Kulikov, I. M., Moskovsky, A. A., Epifanovsky, E., and Kudryavtsev, A. Performance evaluation of the intel optane DC memory with scientific benchmarks. In 2019 IEEE/ACM Workshop on Memory Centric High Performance Computing, MCHPC@SC 2019, Denver, CO, USA, November 18, 2019. IEEE, USA, pp. 1–6, 2019.
Nambiar, R. O. and Poess, M. The making of TPC-DS. In Proceedings of the 32nd International Conference on Very Large Data Bases, Seoul, Korea, September 12-15, 2006, U. Dayal, K. Whang, D. B. Lomet, G. Alonso, G. M. Lohman, M. L. Kersten, S. K. Cha, and Y. Kim (Eds.). ACM, Korea, pp. 1049–1058, 2006.
NVM Express, I. Nvm-express revision 1_4a base specification © 2007 to 2019 nvm express, inc. all rights reserved. https://nvmexpress.org/developers/nvme-specification/, 2019.
Praciano, F. D. B. S., de Sousa, J. F. L., and Machado, J. C. Uma análise experimental da utilização de diferentes tecnologias de armazenamento em um SGBD relacional. In XXXIV Simpósio Brasileiro de Banco de Dados, SBBD 2019, Fortaleza, CE, Brazil, October 7-10, 2019. SBC, Brazil, pp. 259–264, 2019.
Ramakrishnan, R. and Gehrke, J. Database Management Systems. McGraw-Hill, Inc., USA, 2002.
Rayner, N., Feinberg, D., Pezzini, M., and Edjlali, R. Hybrid transaction/analytical processing will foster opportunities for dramatic business innovation. https://www.gartner.com/doc/2657815/hybrid-transactionanalyticalprocessing-foster-opportunities, 2014. Accessed: 2020-10-28.
Shah, M. A., Harizopoulos, S., Wiener, J. L., and Graefe, G. Fast scans and joins using flash drives. In 4th Workshop on Data Management on New Hardware, DaMoN 2008, Vancouver, BC, Canada, June 13, 2008, Q. Luo and K. A. Ross (Eds.). ACM, Canada, pp. 17–24, 2008.
Transaction Processing Performance Council (TPC). TPC BENCHMARKTMC Standard Specification Revision 5.11 © 2010 Transaction Processing Performance Council All Rights Reserved. http://www.tpc.org/TPC_Documents_Current_Versions/pdf/tpc-c_v5.11.0.pdf, 2010.
Transaction Processing Performance Council (TPC). TPC BENCHMARKTMDS Standard Specification Revision 2.13.0 © 2020 Transaction Processing Performance Council All Rights Reserved. http://www.tpc.org/TPC_Documents_Current_Versions/pdf/TPC-DS_v2.13.0.pdf, 2020.
Wu, K., Arpaci-Dusseau, A., Arpaci-Dusseau, R., Sen, R., and Park, K. Exploiting intel optane ssd for microsoft sql server. In Proceedings of the 15th International Workshop on Data Management on New Hardware. DaMoN’19. Association for Computing Machinery, New York, NY, USA, 2019.
Xu, Q., Siyamwala, H., Ghosh, M., Suri, T., Awasthi, M., Guz, Z., Shayesteh, A., and Balakrishnan, V. 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, D. Naor, G. Heiser, and I. Keidar (Eds.). ACM, Israel, pp. 6:1–6:11, 2015.
Zukowski, M. Balancing vectorized query execution with bandwidth-optimized storage, 2009.
