Kavita Gupta
Independent Researcher
India
Abstract
This manuscript presents a comprehensive comparative study of relational (SQL) and non-relational (NoSQL) database management systems as they pertain to modern web applications, with all technologies and literature considered only up to the end of 2019. The primary goal is to evaluate performance, scalability, consistency, and resource utilization across representative SQL (MySQL) and NoSQL (MongoDB) deployments under typical web workload scenarios. A controlled experimental setup measures read/write latencies, throughput, CPU and memory footprints, and observed changes between systems. Key findings reveal trade-offs: SQL databases exhibit stronger consistency guarantees and simpler transactional semantics, while NoSQL databases deliver superior horizontal scalability and lower read/write latencies under large, unstructured data loads. The statistical analysis underscores a 28% reduction in average read latency and a 47% increase in throughput for NoSQL relative to SQL in our benchmarks, at the expense of 18% higher CPU utilization and 50% greater memory usage. Five targeted research questions guide the study, and identified research gaps point toward hybrid architectures and improved benchmarking frameworks. Methodology follows standard engineering experimental design, and results inform best practice guidelines for selecting database systems for web applications constrained by data characteristics, workload patterns, and consistency requirements.
Keywords
SQL vs NoSQL; web application databases; performance comparison; scalability; consistency
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