Stanford Database Library of American Journal of Applied Science and Technology

Vol. 5 No. 11 (2025)
Articles

A Comprehensive Analysis of SQL Code Quality, Performance Optimization, and Multi-Model Database Integration

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  • John E. Maxwell
John E. Maxwell
Department of Computer Science, University of Edinburgh, United Kingdom

Published 2025-11-30

Keywords

  • SQL optimization,
  • code smells,
  • relational databases,
  • multi-model systems

How to Cite

John E. Maxwell. (2025). A Comprehensive Analysis of SQL Code Quality, Performance Optimization, and Multi-Model Database Integration. Stanford Database Library of American Journal of Applied Science and Technology, 5(11), 244–247. Retrieved from https://oscarpubhouse.com/index.php/sdlajast/article/view/39

Copyright (c) 2025 John E. Maxwell

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

The evolving landscape of database systems has prompted a comprehensive examination of SQL code quality, relational and non-relational paradigms, and emerging hybrid frameworks. This study synthesizes insights from foundational relational database theory, object-relational metrics, code quality assessments, and contemporary advances in multi-model database integration. Emphasis is placed on identifying structural inefficiencies, commonly referred to as “code smells,” their impact on database performance, and the practical approaches to remediation in both transactional and analytical contexts. The paper further investigates normalization strategies in nested relational databases, materialized view selection for query optimization, and the emergent convergence of graph and relational query frameworks. By leveraging theoretical models alongside empirical studies of high-performance computing failures and PostgreSQL latency optimization, this research provides a holistic understanding of both classical and modern database systems. Implications for database schema design, query performance, and cross-platform interoperability are explored, highlighting future directions for database engineering, especially in scenarios where NoSQL and NewSQL architectures intersect with traditional relational models.

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