Optimizing Database Performance for Large-Scale Enterprise Applications

Yash Jani

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.

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

How to Cite?: Yash Jani, "Optimizing Database Performance for Large-Scale Enterprise Applications", Volume 11 Issue 10, October 2022, International Journal of Science and Research (IJSR), Pages: 1394-1396, https://www.ijsr.net/getabstract.php?paperid=SR24716121211, DOI: https://dx.doi.org/10.21275/SR24716121211