A literature review on NoSQL database for big data processing

  • Authors

    • Md. Razu Ahmed Daffodil International University
    • Mst. Arifa Khatun
    • Md. Asraf Ali
    • Kenneth Sundaraj
    2018-06-05
    https://doi.org/10.14419/ijet.v7i2.12113
  • Big Data, Data Processing, Hadoop, Mongo DB, NoSQL.

  • Objective: Aim of the present study was to literature review on the NoSQL Database for Big Data processing including the structural issues and the real-time data mining techniques to extract the estimated valuable information.

    Methods: We searched the Springer Link and IEEE Xplore online databases for articles published in English language during the last seven years (between January 2011 and December 2017). We specifically searched for two keywords (“NoSQL†and “Big Dataâ€) to find the articles. The inclusion criteria were articles on the use of performance comparison on valuable information processing in the field of Big Data through NoSQL databases.

    Results: In the 18 selected articles, this review identified 8 articles which provided various suitable recommendations on NoSQL databases for specific area focus on the value chain of Big Data, 5 articles described the performance comparison of different NoSQL databases, 2 articles presented the background of basics characteristics data model for NoSQL, 1 article denoted the storage in respect of cloud computing and 2 articles focused the transactions of NoSQL.

    Conclusion: In this literature, we presented the NoSQL databases for Big Data processing including its transactional and structural issues. Additionally, we highlight research directions and challenges in relation to Big Data processing. Therefore, we believe that the information contained in this review will incredible support and guide the progress of the Big Data processing.

     

     

  • References

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    Razu Ahmed, M., Arifa Khatun, M., Asraf Ali, M., & Sundaraj, K. (2018). A literature review on NoSQL database for big data processing. International Journal of Engineering & Technology, 7(2), 902-906. https://doi.org/10.14419/ijet.v7i2.12113