INTEGRATING GRAPH DATABASE MODELING INTO AGILE SYSTEM ANALYSIS AND DESIGN: A CONCEPTUAL FRAMEWORK FOR SCALABLE INFORMATION SYSTEMS
DOI:
https://doi.org/10.53555/wfehqv74Keywords:
graph database modeling, agile system analysis and design, property graph model, schema evolution, scalable information systems, iterative developmentAbstract
Relational database modeling is still the most popular in system analysis and design (SAD), but has structural constraints in relationship-intensive domains like social networks, fraud detection, recommendation systems, and knowledge graphs (Angles & Gutierrez, 2008; Robinson et al., 2015). These constraints are aggravated in agile systems with iterative delivery and emergent design (Beck et al., 2001; Fowler, 2002; Schwaber & Sutherland, 2017), in which architectural decisions that are susceptible to traversal are often deferred.
This study presents the Graph-Agile Framework, a design science artifact that brings the concepts of graph database modeling into agile SAD using a three-tier architecture: Strategic Alignment, Tactical Integration, and Operational Adaptation. Grounded in design science research and theory synthesis (Gregor & Hevner, 2013; Hevner et al., 2004; Jaakkola, 2020a), the framework institutionalizes traversal-aware reasoning, schema optionality, and sprint-level scalability validation into the iterative workflows.
An expert-based evaluation (N = 40) assessed structural clarity, theoretical grounding, agile alignment, scalability support, and adoption feasibility. Findings indicate consistently high expert-rated internal coherence and compatibility with agile practices, providing preliminary perceptual support for the framework’s utility.
The study advances SAD theory beyond relational assumptions and extends agile methodology by formalizing traversal-aware architectural governance for scalable graph-centric system development.
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