UML4NoSQL: A Novel Approach for Modeling NoSQL Document-Oriented Databases Based on UML - Maicha, Mohammed ElHabib; Ouinten, Youcef; Ziani, Benameur (Computing and Informatics, 2022)
The adoption of Big Data systems by the companies is relatively new, although the data modeling and system design are ages old. Despite the fact that traditional databases are built on solid foundations, they cannot handle the swift and massive flow of data coming from multiple different sources. Herein, NoSQL databases are an inevitable alternative. However, these systems are schemaless compared to traditional databases. It is important to emphasize that schemaless does not mean no-schema which would mean that NoSQL databases do not need modeling. Hence, there is a need for conceptual models to define the data structure in these databases. This paper sheds a light on the importance of the UML in showing how to store Big Data described through meta-models within NoSQL databases. We propose a novel Big Data modeling methodology for NoSQL databases called UML4NoSQL, which is independent of the target system, and taking into account the four Big Data characteristics: Variety, Volume, Velocity, and Veracity (4 V's). The approach relies on the UML blocks with a data-up technique; it starts with a use-case and the class diagram resulting from the understanding of the data at hand and the definition of the developer's strategies while focusing on the user's needs. To illustrate our approach, we take a case study from health care domain. We show that our approach produces designs that can be implemented on NoSQL document-oriented system with respect to Big Data 4 V's.