Abstract
For very years, relational databases have been the leading model for data storage, retrieval and management. However, due to increasing needs for scalability and performance, alternative systems have emerged, namely NewSQL technology. NewSQL is a class of modern relational database management systems (RDBMS) that provide the same scalable performance of NoSQL systems for online transaction processing (OLTP) read-write workloads, while still maintaining the ACID guarantees of a traditional database system. In this research paper, the performance of a NewSQL database is evaluated, compared to a MySQL database, both running in the cloud, in order to measure the response time against different configurations of workloads.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barrionuevo, M., et al.: Estrategias y análisis orientados al manejo de datos masivos usando computación de alto desempeño (2018). http://sedici.unlp.edu.ar/handle/10915/68233
Marr, B.: How much data do we create every day? The mind-blowing stats everyone should read (n.d.). https://www.forbes.com/sites/bernardmarr/2018/05/21/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read/#61fd023f60ba. Accessed 18 Mar 2019
Corbett, J.C., et al.: Spanner: Google’s globally distributed database. ACM Trans. Comput. Syst. (TOCS) 31(3), 8 (2013). https://doi.org/10.1145/2491245
Google: Google Cloud Platform Overview—Overview—Google Cloud (n.d.). https://cloud.google.com/docs/overview/. Accessed 1 Apr 2019
Google: Cloud Spanner Documentation (2017)
Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M.: Internet of Things (IoT): a vision, architectural elements, and future directions. Future Gener. Comput. Syst. 29(7), 1645–1660 (2013). https://doi.org/10.1016/J.FUTURE.2013.01.010
Hashem, I.A.T., Yaqoob, I., Anuar, N.B., Mokhtar, S., Gani, A., Ullah Khan, S.: The rise of “big data” on cloud computing: review and open research issues. Inf. Syst. 47, 98–115 (2015). https://doi.org/10.1016/J.IS.2014.07.006
Han, J., Haihong, E., Le, G., Du. J.: Survey on NoSQL database. In: 2011 6th International Conference on Pervasive Computing and Applications, pp. 363–366. IEEE (2011). https://doi.org/10.1109/ICPCA.2011.6106531
Kacfah Emani, C., Cullot, N., Nicolle, C.: Understandable big data: a survey. Comput. Sci. Rev. 17, 70–81 (2015). https://doi.org/10.1016/j.cosrev.2015.05.002
Kumar, R., Gupta, N., Maharwal, H., Charu, S., Yadav, K.: Critical analysis of database management using NewSQL. Int. J. Comput. Sci. Mob. Comput. 35(5), 434–438 (2014). http://s3.amazonaws.com/academia.edu.documents/33752078/V3I5201499a2.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1495314606&Signature=VhHyc%2BR0An%2FF8Oa6W5EAkCgxO9c%3D&response-content-disposition=inline%3Bfilename%3DCritical_Analysis_of_Database_Management.pdf
Liu, H.: Big data drives cloud adoption in enterprise. IEEE Internet Comput. 17(4), 68–71 (2013). https://doi.org/10.1109/MIC.2013.63
Madden, S.: From databases to big data. IEEE Internet Comput. 16(3), 4–6 (2012). https://doi.org/10.1109/MIC.2012.50
McFadyen, R., Kanabar, V.: An Introduction to Structured Query Language. Wm. C. Brown, Dubuque (1991). https://dl.acm.org/citation.cfm?id=102896
Mell, P., Grance, T.: The NIST Definition of Cloud Computing (2011)
Moniruzzaman, A.B.M.: NewSQL: towards next-generation scalable RDBMS for online transaction processing (OLTP) for big data management (2014). http://arxiv.org/abs/1411.7343
Mukherjee, S., Mishra, M.K., Mishra, B.S.P.: Promises and Challenges of Big Data in a Data-Driven World. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds.) Emerging Technologies in Data Mining and Information Security. AISC, vol. 813, pp. 201–211. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-1498-8_18
NIST: NIST Big Data Working Group (NBD-WG) (n.d.). https://bigdatawg.nist.gov/home.php. Accessed 18 Mar 2019
Oussous, A., Benjelloun, F.-Z., Ait Lahcen, A., Belfkih, S.: Big data technologies: a survey. J. King Saud Univ.-Comput. Inf. Sci. 30(4), 431–448 (2018). https://doi.org/10.1016/J.JKSUCI.2017.06.001
Plattner, H.: A common database approach for OLTP and OLAP using an in-memory column database. In: Proceedings of the 35th SIGMOD International Conference on Management of Data - SIGMOD 2009, pp. 1–2. ACM Press, New York (2009). https://doi.org/10.1145/1559845.1559846
Pokorný, J.: Database technologies in the world of big data. In: Proceedings of the 16th International Conference on Computer Systems and Technologies - CompSysTech 2015, pp. 1–12. ACM Press, New York (2015). https://doi.org/10.1145/2812428.2812429
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Murazzo, M., Gómez, P., Rodríguez, N., Medel, D. (2019). Database NewSQL Performance Evaluation for Big Data in the Public Cloud. In: Naiouf, M., Chichizola, F., Rucci, E. (eds) Cloud Computing and Big Data. JCC&BD 2019. Communications in Computer and Information Science, vol 1050. Springer, Cham. https://doi.org/10.1007/978-3-030-27713-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-030-27713-0_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27712-3
Online ISBN: 978-3-030-27713-0
eBook Packages: Computer ScienceComputer Science (R0)