Performance and Security Evaluation of DBMS Models for E-Commerce and Website Session Tracking

The exponential increase of data within businesses has a substantial impact on the performance of database management systems. As businesses deal with growing volumes of data, selecting the correct DBMS becomes critical to ensuring efficiency and data integrity. In this paper, we present our experimental insights into how different data models utilized by database management systems (DBMS) perform under varying conditions, using two scenarios: Sales Performance Analysis and Real-Time Analytics for Web Traffic. This paper examines the various data models used by DBMS, notably MySQL (Relational Model), MongoDB (Document-Based Model), Redis (Key-Value Model), Cassandra (Wide Column Model), and Neo4j (Graph Model). We evaluate the strengths and limitations of these data models in terms of data creation, manipulation, retrieval, and database security measures such as access control and data integrity for each scenario. The findings provide useful information for optimizing DBMS selection to improve data management and operational effectiveness in the face of increasing data demands.