Performance Analysis of Scaling NoSQL vs SQL: A Comparative Study of MongoDB, Cassandra, and PostgreSQL

D. Yedilkhan, A. Mukasheva, Dariya Bissengaliyeva, Yerulan Suynullayev
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Abstract

This study aims to investigate state-of-the-art methods for scalable database management, focusing on cost-effectiveness. The study compares two commonly used NoSQL databases, MongoDB, and Cassandra DB, with a traditional relational database management system, PostgreSQL. The comparison is made through performance evaluations conducted on multiple clusters encompassing cloud and on-premises environments. The evaluations include database operations such as insertion, selection, and deletion. The study results indicate that each database management system is optimized for particular use cases. The choice must be based on a comprehensive assessment of multiple factors, not limited to scalability and performance. The novelty of this study lies in its scalability comparison of three popular database management systems and its emphasis on cost-effectiveness while evaluating performance in different environments.
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伸缩NoSQL与SQL的性能分析:MongoDB, Cassandra和PostgreSQL的比较研究
本研究旨在研究可扩展数据库管理的最先进方法,重点关注成本效益。该研究将两种常用的NoSQL数据库MongoDB和Cassandra DB与传统的关系数据库管理系统PostgreSQL进行了比较。通过对包含云和本地环境的多个集群进行性能评估来进行比较。评估包括数据库操作,如插入、选择和删除。研究结果表明,每个数据库管理系统都针对特定的用例进行了优化。选择必须基于对多种因素的综合评估,而不限于可伸缩性和性能。这项研究的新颖之处在于它比较了三种流行的数据库管理系统的可伸缩性,并且在评估不同环境下的性能时强调了成本效益。
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