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Optimizing Database Performance for Large-Scale Enterprise Applications

Journal: International Journal of Science and Research (IJSR) (Vol.11, No. 10)

Publication Date:

Authors : ;

Page : 1394-1396

Keywords : automated query optimizers; refactoring queries; parameterization; limiting result sets; caching; in-memory caching; distributed caching; hybrid caching;

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Abstract

In the digital transformation era, large-scale enterprise applications are the backbone of many organizations. Efficient database performance is crucial for these applications to ensure quick data retrieval, seamless user experience, and robust backend operations. This paper explores advanced strategies for optimizing database performance, focusing on indexing, query optimization, caching, multithreading, and the utilization of NoSQL databases like MongoDB. By addressing these aspects, enterprises can enhance their database systems' scalability, reliability, and efficiency, ultimately driving better business outcomes.

Last modified: 2025-09-22 21:31:24