Abstract

Software systems developed over the past decade were traditionally designed to incorporate relational databases for managing their data requirements. However, relational databases increasingly struggle to handle the growing volume, velocity, and variety of data in modern applications. In response, document-oriented NoSQL databases—such as MongoDB— have progressively emerged as a compelling alternative, offering greater flexibility and scalability for managing semi-structured data. This paradigm shift has necessitated the migration of existing systems to NoSQL architectures. This paper presents a comprehensive review of migration strategies and methodologies for transitioning from relational databases to document-oriented NoSQL systems. It examines key components of the migration process, including schema conversion, data transformation, and query refactoring, while evaluating existing tools and techniques in terms of automation, scalability, and data integrity. The study identifies unresolved research challenges, including semantic preservation, schema evolution, and tool interoperability, and proposes future directions, such as AI-assisted migration planning. Overall, this paper highlights key research gaps to help researchers support the development of reliable, scalable, and semantically robust migration solutions.

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