NoSQL Database Selection Process: An Integrated Proof of Concept and Comparison for Targeted Document Store Databases

NoSQL Database Selection Process: An Integrated Proof of Concept and Comparison for Targeted Document Store Databases

연구 분야: Databases

학회: 2025 4th International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)

The study offers an analysis of NoSQL document store databases focusing on MongoDB, Couchbase, and CouchDB and includes an integrated Proof of Concept (POC) along with a research-based comparison. It begins with an overview of the evolving landscape of Database Management Systems (DBMS) highlighting the role of NoSQL databases in overcoming the limitations of traditional relational databases. The research includes a contextual evaluation and qualitative comparison of the three databases incorporating performance metrics to gauge their suitability for various applications. MongoDB is identified as the best in query performance (1.5 ms), transaction support, and integration with cloud platforms. Couchbase shows competitive scalability and good query performance (2.6ms) while CouchDB lacks ACID transactions, optimization, and support barriers and shows query time (6 ms), This analysis highlights each database's strengths and weaknesses providing key insights for real-world deployment.