Development of the Unified Database Design Methodology for Big Data Applications - based on MongoDB -

Jun-Ho Lee (이준호); Joo Kyung-Soo (주경수)

doi:10.9708/jksci.2018.23.03.041

Development of the Unified Database Design Methodology for Big Data Applications - based on MongoDB -

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2018, 23(3), pp.41-48
DOI : 10.9708/jksci.2018.23.03.041
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : January 25, 2018
Accepted : February 28, 2018
Published : March 30, 2018

Jun-Ho Lee ¹, Joo Kyung-Soo ¹

¹순천향대학교

Accredited

ABSTRACT

The recent sudden increase of big data has characteristics such as continuous generation of data, large amount, and unstructured format. The existing relational database technologies are inadequate to handle such big data due to the limited processing speed and the significant storage expansion cost. Current implemented solutions are mainly based on relational database that are no longer adapted to these data volume. NoSQL solutions allow us to consider new approaches for data warehousing, especially from the multidimensional data management point of view. In this paper, we develop and propose the integrated design methodology based on MongoDB for big data applications. The proposed methodology is more scalable than the existing methodology, so it is easy to handle big data.

KEYWORDS

Database, NoSQL, MongoDB, Design Methodology

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* References for papers published after 2023 are currently being built.

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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Development of the Unified Database Design Methodology for Big Data Applications - based on MongoDB -

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Development of the Unified Database Design Methodology for Big Data Applications - based on MongoDB -

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.