Comparisons Between MongoDB and MS-SQL Databases on the TWC Website
American Journal of Software Engineering and Applications
Volume 4, Issue 2, April 2015, Pages: 35-41
Received: Feb. 16, 2015;
Accepted: Apr. 22, 2015;
Published: May 5, 2015
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Chieh Ming Wu, Dept. of Computer Science, Taiwan Water Corporation, Taichung City, Taiwan
Yin Fu Huang, School of Computer Science & Information Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin, Taiwan
John Lee, Dept. of Sales, Formula Chemicals Corporation, New Taipei City, Shulin District, Taiwan
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Owing to the huge amount of data in websites to be analysed, web innovative services are required to support them with high scalability and availability. The main reason of using NoSQL databases is for considering the huge amount of data and expressing large-scale distributed computations using Map-Reduce techniques. To enhance the service quality of customers and solve the problems of the huge amount of data existing in the websites such as Facebook, Google, and Twitter, the relational database technology was gradually replaced with the NoSQL database to improve the performance and expansion elasticity in recent years. In this paper, we compare both NoSQL MongoDB and MS-SQL databases, and discuss the effectiveness of the inquiry. In addition, relational database cluster systems often require larger server efficiency and capacity to be competent, but it incurs cost problems. On the other hand, using NoSQL database can easily expand the capacity without any extra costs. Through the experiments, it shows that NoSQL MongoDB is about ten times efficient for reading and writing than MS-SQL database. This verifies that the NoSQL database technology is quite a feasible option to be used in the future.
NoSQL, MS-SQL, MongoDB, Relational Database
To cite this article
Chieh Ming Wu,
Yin Fu Huang,
Comparisons Between MongoDB and MS-SQL Databases on the TWC Website, American Journal of Software Engineering and Applications.
Vol. 4, No. 2,
2015, pp. 35-41.
Bonnet, L.;Laurent, A.;Sala, M.;Laurent, B., REDUCE, YOU SAY: What NoSQL can do for Data Aggregation and BI in Large Repositories, 22nd International Workshop on Database and Expert Systems Applications (DEXA), pp. 483-488, 2011.
J. Dean, S. Ghemawat. Mapreduce: simplified data processing on large clusters, Commun. ACM, pp.107-113, 2008.
Kristina Chodorow & Michael Dirolf, MongoDB: The Definitive Guide , O'Reilly Media, 2012.
Liu Yimeng; Wang Yizhi; Jin Yi, Research on The Improvement of MongoDB Auto-Sharding in Cloud Environment, 7th International Conference on Computer Science & Education (ICCSE), pp. 851- 854, 2012.
Lawrence, R., Integration and Virtualization of Relational SQL and NoSQL Systems including MySQL and MongoDB, International Conference on Computational Science and Computational Intelligence, pp.285-290, 2014.
Nyati, S.S. ; Pawar, S. ; Ingle, R., Performance Evaluation of Unstructured NoSQL data over distributed framework, International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1623-1627, 2014.
Okman, L. ; Gal-Oz, N. ; Gonen, Y. ; Gudes, E. ; Abramov, J., "Security Issues in NoSQL Databases", IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pp. 541 – 547, 2011.
Pramod J. Sadalage, Martin Fowler, "NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence", Addison-Wesley Professional, 2012.
Wang Xiaolin ; Chen Haopeng ; Wang Zhenhua, "Research on Improvement of Dynamic Load Balancing in MongoDB", IEEE 11th International Conference on Dependable, Autonomic and Secure Computing (DASC), pp.124-130, 2013.