Bridging the Gap: A Systematic Review of UML-Based Modeling for NoSQL Databases

Abstract

The increasing adoption of NoSQL databases to manage diverse and complex data structures necessitates robust modeling techniques. The Unified Modeling Language (UML), traditionally utilized for relational databases, has emerged as a promising tool for modeling NoSQL databases, despite their flexible and schemaless nature. This paper presents a comprehensive exploration of UML's role in NoSQL data modeling through a systematic literature review (SLR). Key contributions include an extensive bibliometric analysis of UML applications across various types of NoSQL databases, as well as the identification of trends and gaps in current methodologies. The discussion highlights UML's strengths in the initial stages of conceptualizing data structures while addressing its limitations in representing the dynamic and distributed characteristics inherent to NoSQL systems. Novel insights are provided into the adaptation of UML for logical and physical modeling in document-oriented, graph-based, and columnar databases. The work concludes with actionable recommendations for enhancing UML-based methodologies and outlines future research directions to tackle unresolved challenges in this rapidly evolving field.