Comparative Analysis of Performance of Relational and NoSQL Database Systems in E-Commerce Information Applications

Abstract

The rapid development of information technology has driven the need for a database system that is able to manage data efficiently, especially in e-commerce information applications that have large and dynamic data volumes. This study aims to analyze and compare the performance of relational database systems (RDBMS) with NoSQL databases in the context of e-commerce applications. The research is carried out with a qualitative approach through the literature study method or library research that examines various academic sources, including journals, books, and previous research reports. The analysis was carried out on several key performance aspects, such as scalability, speed of data access, flexibility of data structure, and ability to handle big data. The results show that relational databases still excel in the consistency of complex data and transactions, but have limitations in terms of horizontal scalability. On the other hand, NoSQL databases, such as MongoDB and Cassandra, show better performance in handling unstructured, large-scale data, and fast access needs, although at the expense of some aspects of consistency. These findings indicate that the selection of database types needs to be adjusted to the needs of the system and the characteristics of the data managed. This study makes a theoretical contribution to understanding the comparative performance of the two systems and becomes a reference for e-commerce system developers in determining the optimal database architecture.