The Role of AI in Predictive Database Performance Tuning

The integration of artificial intelligence into database performance tuning marks a pivotal evolution in data management practices. As traditional manual approaches by Database Administrators give way to predictive and autonomous systems, organizations are experiencing transformative benefits across multiple dimensions of database operations. AI technologies now enable workload prediction, automated indexing, anomaly detection, and resource optimization that far exceed human capabilities in both accuracy and efficiency. While challenges exist in implementing these systems—particularly regarding continuous learning requirements and legacy database integration—the trajectory toward fully autonomous database management continues to accelerate. This advancement fundamentally shifts the role of database professionals from routine maintenance to strategic data architecture and innovation, ultimately promising a future where databases self-optimize with minimal human oversight while delivering superior performance and reliability.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-03-06
DOI
https://doi.org/10.32628/cseit25112365
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

The Role of AI in Predictive Database Performance Tuning

Ellavarasan Asokan
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Big Data and Business Intelligence
article

The Role of AI in Predictive Database Performance Tuning

Ellavarasan Asokan
article en

Abstract

The integration of artificial intelligence into database performance tuning marks a pivotal evolution in data management practices. As traditional manual approaches by Database Administrators give way to predictive and autonomous systems, organizations are experiencing transformative benefits across multiple dimensions of database operations. AI technologies now enable workload prediction, automated indexing, anomaly detection, and resource optimization that far exceed human capabilities in both accuracy and efficiency. While challenges exist in implementing these systems—particularly regarding continuous learning requirements and legacy database integration—the trajectory toward fully autonomous database management continues to accelerate. This advancement fundamentally shifts the role of database professionals from routine maintenance to strategic data architecture and innovation, ultimately promising a future where databases self-optimize with minimal human oversight while delivering superior performance and reliability.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(2)
Anna University, Chennai (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 94%
Big Data and Business Intelligence
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The Role of AI in Predictive Database Performance Tuning — Ellavarasan Asokan · International Journal of Scientific Research in Computer Science Engineering and Information Technology (2025) | TGRS Research Map | TGRS