Research Article

Database Evolution: The Transformation of Data Partitioning and Indexing in the Cloud Era

Authors

  • Purushotham Jinka University of Arizona Global Campus, USA

Abstract

Cloud computing has revolutionized database management systems, transforming traditional approaches to data partitioning and indexing strategies. The shift from on-premises to cloud-native solutions has introduced automated scaling, dynamic resource allocation, and intelligent workload distribution mechanisms. This transformation has enabled organizations to achieve higher availability, improved performance, and reduced operational costs. The evolution encompasses machine learning-driven optimizations, enhanced cross-region data distribution, and advanced predictive scaling capabilities, fundamentally changing how databases are designed, deployed, and managed in modern applications. The integration of artificial intelligence and automation has further enhanced database operations, enabling real-time optimization, predictive maintenance, and autonomous decision-making capabilities while ensuring data consistency and reliability across distributed environments. These advancements have redefined the boundaries of database management, creating more resilient and adaptive systems capable of meeting evolving business demands.

Article information

Journal

Journal of Computer Science and Technology Studies

Volume (Issue)

7 (5)

Pages

16-22

Published

2025-05-29

How to Cite

Purushotham Jinka. (2025). Database Evolution: The Transformation of Data Partitioning and Indexing in the Cloud Era. Journal of Computer Science and Technology Studies, 7(5), 16-22. https://doi.org/10.32996/jcsts.2025.7.5.3

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Keywords:

Cloud-native databases, Dynamic partitioning, Automated indexing, Machine learning optimization, Resource elasticity