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Comparisons Between MongoDB and MS-SQL Databases on the TWC Website

Received: 16 February 2015     Accepted: 22 April 2015     Published: 5 May 2015
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Abstract

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.

Published in American Journal of Software Engineering and Applications (Volume 4, Issue 2)
DOI 10.11648/j.ajsea.20150402.12
Page(s) 35-41
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

NoSQL, MS-SQL, MongoDB, Relational Database

References
[1] 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.
[2] J. Dean, S. Ghemawat. Mapreduce: simplified data processing on large clusters, Commun. ACM, pp.107-113, 2008.
[3] Kristina Chodorow & Michael Dirolf, MongoDB: The Definitive Guide , O'Reilly Media, 2012.
[4] 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.
[5] 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.
[6] Nakabasami, K.; Amagasa, T.; Kitagawa, H., "Querying MongoDB with LINQ in a Server-Side JavaScript Environment", 16th International Conference on Network-Based Information Systems (NBiS), pp.344-349, 2013.
[7] 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.
[8] 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.
[9] Pramod J. Sadalage, Martin Fowler, "NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence", Addison-Wesley Professional, 2012.
[10] 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.
Cite This Article
  • APA Style

    Chieh Ming Wu, Yin Fu Huang, John Lee. (2015). Comparisons Between MongoDB and MS-SQL Databases on the TWC Website. American Journal of Software Engineering and Applications, 4(2), 35-41. https://doi.org/10.11648/j.ajsea.20150402.12

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    ACS Style

    Chieh Ming Wu; Yin Fu Huang; John Lee. Comparisons Between MongoDB and MS-SQL Databases on the TWC Website. Am. J. Softw. Eng. Appl. 2015, 4(2), 35-41. doi: 10.11648/j.ajsea.20150402.12

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    AMA Style

    Chieh Ming Wu, Yin Fu Huang, John Lee. Comparisons Between MongoDB and MS-SQL Databases on the TWC Website. Am J Softw Eng Appl. 2015;4(2):35-41. doi: 10.11648/j.ajsea.20150402.12

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  • @article{10.11648/j.ajsea.20150402.12,
      author = {Chieh Ming Wu and Yin Fu Huang and John Lee},
      title = {Comparisons Between MongoDB and MS-SQL Databases on the TWC Website},
      journal = {American Journal of Software Engineering and Applications},
      volume = {4},
      number = {2},
      pages = {35-41},
      doi = {10.11648/j.ajsea.20150402.12},
      url = {https://doi.org/10.11648/j.ajsea.20150402.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20150402.12},
      abstract = {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.},
     year = {2015}
    }
    

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    AU  - Chieh Ming Wu
    AU  - Yin Fu Huang
    AU  - John Lee
    Y1  - 2015/05/05
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    DO  - 10.11648/j.ajsea.20150402.12
    T2  - American Journal of Software Engineering and Applications
    JF  - American Journal of Software Engineering and Applications
    JO  - American Journal of Software Engineering and Applications
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    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.ajsea.20150402.12
    AB  - 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.
    VL  - 4
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Author Information
  • Dept. of Computer Science, Taiwan Water Corporation, Taichung City, Taiwan

  • School of Computer Science & Information Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin, Taiwan

  • Dept. of Sales, Formula Chemicals Corporation, New Taipei City, Shulin District, Taiwan

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