Optimizing database queries: Cost and performance analysis
Vasudevan Senathi Ramdoss · International Journal of Science and Research Archive · 2021
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.