A Model for a Serialized Set-Oriented NoSQL Database Management System

Recent advancements in data management highlight the increasing focus on large-scale integration and analytics, with the management of duplicate information becoming a more resource-intensive and costly task. Existing SQL and NoSQL systems inadequately address the semantic constraints of set-based data, either by compromising relational fidelity or through inefficient deduplication mechanisms. This paper presents a set-oriented centralized NoSQL database management system (DBMS) that enforces uniqueness by construction, thereby reducing downstream deduplication and enhancing result determinism. The system utilizes in-memory execution with binary serialized persistence, achieving O(1) time complexity for exact-match CRUD operations while maintaining ACID-compliant transactional semantics through explicit commit operations. A comparative performance evaluation against Redis and MongoDB highlights the trade-offs between consistency guarantees and latency. The results reveal that enforced set uniqueness completely eliminates duplicates, incurring only moderate latency trade-offs compared to in-memory performance measures. The model can be extended for fuzzy queries and imprecise data by retrieving the membership function information. This work demonstrates that the set-oriented DBMS design represents a distinct architectural paradigm that addresses data integrity constraints inadequately handled by contemporary database systems.