Optimizing Database Performance: Strategies for Efficient Query Execution and Resource Utilization |
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| © 2023 by IJCTT Journal | ||
| Volume-71 Issue-7 |
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| Year of Publication : 2023 | ||
| Authors : Vivek Basavegowda Ramu | ||
| DOI : 10.14445/22312803/IJCTT-V71I7P103 | ||
How to Cite?
Vivek Basavegowda Ramu, "Optimizing Database Performance: Strategies for Efficient Query Execution and Resource Utilization," International Journal of Computer Trends and Technology, vol. 71, no. 7, pp. 15-21, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I7P103
Abstract
In today's world, which is highly driven by data, where information serves as a lifeblood of organizations, optimizing database performance is of utmost importance. Effective query management and resource management are critical to optimize system performance and ensure the best possible user experience. This paper explores various methods and techniques for improving the performance of databases without compromising data integrity or security. Drawing on extensive research and expert insights, we delve into the intricacies of query execution optimization. We examine various approaches, such as query rewriting, indexing, and caching, to minimize query response times and improve overall system throughput. By leveraging these techniques, database administrators and developers can fine-tune query execution plans, reducing the need for resource-intensive operations and enhancing overall system efficiency. Resource utilization plays a critical role in maximizing database performance. We delve into strategies for effective resource management, including memory allocation, disk I/O optimization, and parallel processing. Through careful resource allocation and optimization, databases can better handle concurrent requests, reduce bottlenecks, and achieve higher throughput. To address the challenges of growing data volumes, we explore techniques for data partitioning, sharding, and replication. These strategies enable horizontal scaling, distributing the data across multiple servers and allowing for efficient parallel processing. We also investigate the impact of database schema design on performance and discuss best practices for schema optimization, including normalization, denormalization, and data aggregation. The paper also delves into the realm of performance monitoring and tuning. We discuss the importance of regular performance profiling, identifying system bottlenecks, and optimizing database configurations. It is possible for the database administrator to proactively identify the areas of improvement and implement targeted optimization, which will result in peak performance of the database by monitoring key metrics like query execution time, CPU usage, and disk I/O rates. The study targets to present a comprehensive overview of strategies and techniques which is required for optimizing database performance. By adopting these strategies, organizations can unleash the full capabilities of their databases, ensure query execution efficiency, maximize resources, and deliver exceptional performance to consume a modern application meeting the ever-increasing demands of data-driven types.
Keywords
Database performance, Query execution, Resource utilization, Optimization strategies, Efficient database.
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