Enhancing Database Query Performance: A Cost Optimization Approach

Vasudevan Senathi Ramdoss

doi:10.30574/ijsra.2021.2.2.0025

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Enhancing Database Query Performance: A Cost Optimization Approach

Vasudevan Senathi Ramdoss ^*

Overland Park, Kansas, USA.

Review Article

International Journal of Science and Research Archive, 2021, 02(02), 293-297.

Article DOI: 10.30574/ijsra.2021.2.2.0025

DOI url: https://doi.org/10.30574/ijsra.2021.2.2.0025

Publication history

Received on 15 March 2021; revised on 20 May 2021; accepted on 23 May 2021

Abstract

Optimizing database query performance is critical for ensuring efficient data management, reducing costs, and improving user experience. Poorly optimized queries can cause slow response times, increased CPU and memory usage, and excessive disk I/O operations, affecting system performance. This paper explores various query optimization techniques, including cost-based analysis, indexing, query rewriting, execution plan analysis, parallel execution, and caching. Additionally, it compares optimization strategies across different database types, including SQL-based relational databases (MySQL, PostgreSQL, Oracle), NoSQL databases (MongoDB, Cassandra), and NewSQL databases (Google Spanner, CockroachDB). Real-world use cases from e-commerce, banking, healthcare, and financial sectors demonstrate the practical applications of these strategies.

Keywords

Database Queries; Query Optimization; SQL; NoSQL; NewSQL; Performance Tuning, Cost Analysis; Execution Plans; Indexing; Query Rewriting; Parallel Execution; Caching

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How to cite this article

Vasudevan Senathi Ramdoss. Enhancing Database Query Performance: A Cost Optimization Approach. International Journal of Science and Research Archive, 2021, 02(02), 293-297. Article DOI: https://doi.org/10.30574/ijsra.2021.2.2.0025

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