Automated cross-environment SQL plan analysis: A rapid response approach to OLTP performance optimization

Krishnakumar, Diwakar (2025) Automated cross-environment SQL plan analysis: A rapid response approach to OLTP performance optimization. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 639-644. ISSN 2582-8266

[thumbnail of WJAETS-2025-0225.pdf] Article PDF
WJAETS-2025-0225.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download ( 518kB)

Abstract

This article presents an innovative approach to OLTP database performance optimization through automated cross-environment SQL plan analysis. The article addresses critical challenges in modern enterprise systems where millisecond-level response times directly impact business operations. By implementing a sophisticated framework that leverages database query fingerprinting, execution pattern recognition, and cross-environment analytical capabilities, the solution enables rapid identification and resolution of performance issues. The article automates the collection and analysis of performance metrics across multiple database instances, significantly reducing manual intervention while maintaining accuracy and reliability. The framework incorporates advanced plan profiling and transplantation techniques, ensuring optimal execution patterns are identified and implemented efficiently across different database environments. This comprehensive solution not only minimizes SLA breach durations but also enhances overall DBA efficiency by enabling focus on strategic optimization initiatives rather than routine performance monitoring tasks. The article demonstrates how this automated approach revolutionizes traditional database optimization processes while maintaining system stability and performance consistency.

Item Type: Article
Official URL: https://doi.org/10.30574/wjaets.2025.15.1.0225
Uncontrolled Keywords: Database Performance Optimization; OLTP Systems; Cross-Environment Analysis; SQL Plan Management; Automated Query Optimization
Depositing User: Editor Engineering Section
Date Deposited: 04 Aug 2025 16:02
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/2743