Choosing a database for a cloud application is difficult because published performance results are rarely produced under comparable conditions. This study reviews published evidence on cloud database performance, with primary attention to MySQL and PostgreSQL, and examines how workload mix, concurrency, resource allocation, and deployment configuration shape reported results. The study follows a descriptive, comparative, literature-based methodology. No new cloud benchmark experiments were conducted, and measurements from non-equivalent studies were not pooled. Empirical benchmarks, cloud and architecture studies, and systematic reviews are compared by workload, environment, reported metrics, findings, and limitations. One study on Amazon Web Services reported strong results for managed MySQL under a read-intensive stock market workload, whereas a separate Windows-based benchmark reported lower PostgreSQL execution times in several SELECT scenarios. Because the studies used different datasets, workloads, and deployments, their results do not establish an overall ranking of the two systems. The review also finds that processor, memory, and storage measurements and benchmark configuration details are reported inconsistently. The contribution is an evidence-aware synthesis that supports workload-matched evaluation, multiple performance measures, and transparent reporting.

Akshay Ramesh Dere, Dr. Rupali Kalekar, "Performance Analysis of Cloud-Based Database Systems" International Journal of Advance Research in Science, Management, Engineering and Technology, V1(4): Page(198-209) September - October 2026. ISSN: 3139-1141. www.ijarsmet.com. Published by Scientific and Academic Research Publishing.