Data Modeling Guidelines for NoSQL Document-Store Databases

Abstract

Good database design is key to high data avail-ability and consistency in traditional databases, and numerous techniques exist to abet designers in modeling schemas appropri-ately. These schemas are strictly enforced by traditional database engines. However, with the emergence of schema-free databases (NoSQL) coupled with voluminous and highly diversified datasets (big data), such aid becomes even more important as schemas in NoSQL are enforced by application developers, which requires a high level of competence. Precisely, existing modeling techniques and guides used in traditional databases are insufficient for big-data storage settings. As a synthesis, new modeling guidelines for NoSQL document-store databases are posed. These guidelines cut across both logical and physical stages of database designs. Each is developed based on solid empirical insights, yet they are prepared to be intuitive to developers and practitioners. To realize this goal, we employ an exploratory approach to the investigation of techniques, empirical methods and expert consultations. We analyze how industry experts prioritize requirements and analyze the relationships between datasets on the one hand and error prospects and awareness on the other hand. Few proprietary guidelines were extracted from a heuristic evaluation of 5 NoSQL databases. In this regard, the proposed guidelines have great potential to function as an imperative instrument of knowledge transfer from academia to NoSQL database modeling practices.

Authors and Affiliations

Abdullahi Abubakar Imam, Shuib Basri, Rohiza Ahmad, Junzo Watada, Maria T. Gonzlez-Aparicio, Malek Ahmad Almomani

Keywords

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  • EP ID EP408912
  • DOI 10.14569/IJACSA.2018.091066
  • Views 84
  • Downloads 0

How To Cite

Abdullahi Abubakar Imam, Shuib Basri, Rohiza Ahmad, Junzo Watada, Maria T. Gonzlez-Aparicio, Malek Ahmad Almomani (2018). Data Modeling Guidelines for NoSQL Document-Store Databases. International Journal of Advanced Computer Science & Applications, 9(10), 544-555. https://europub.co.uk/articles/-A-408912