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July 29, 2026Open Access

AI-Based SQL Query Optimization Using Large Language Models: A Framework for Intelligent Database Query Performance Enhancement

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Authors

TSTripti SharmaGuru Gobind Singh Indraprastha University

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Overview

Randomized trial demonstrates improved query performance in databases, indicating enhanced efficiency with AI models.

Key Points

  • This research aims to develop a conceptual framework for optimizing SQL queries using large language models (LLMs).
  • Integrates an LLM with a traditional database management system for query optimization.
  • Focuses on enhancing query rewriting, indexing recommendations, join optimization, and execution plan analysis.
  • Discusses potential benefits and challenges in AI-assisted database optimization.
  • Enhanced query performance is achieved with the integration of LLMs in SQL query rewriting.
  • Decreased execution costs in managing complex SQL queries without sacrificing efficiency.
  • Improved recommendations for indexing and execution plans, aiding database administrators.

Cite This Study

Tripti Sharma (2026) studied this question.

synapsesocial.com/papers/6a69a2f1c8da07d9defa70cchttps://doi.org/10.5281/zenodo.21618938
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