An in-depth Examination of Logical Data Models Utilized in Data Storage Systems to Facilitate Data Modeling

Abstract

Data is a crucial asset in the current era of big data. Organizations collect, store, and analyze data at different scales, velocities, types, and structures to aid their decision-making. Database management systems (DBMS) also play a key role in properly storing large amounts of data. Understanding data models and selecting the appropriate database are essential for achieving scalable storage and efficient query performance. The motivation and main purposes behind this work are to present important characteristics of prominent logical models of data storage systems in one place in order to accomplish the following goals: First, providing a detailed guide on logical data models of DBMS, starting from legacy ones to modern contemporary systems, all in one place; secondly, presenting a consolidated and comparative overview of the characteristics of logical data models for researchers, database designers, and developers of data-intensive systems to guide them in selecting the appropriate data storage system for data modeling tasks; and lastly, presenting an overview of popular data storage systems and their data models to illustrate current trends in DBMS.

Keywords

• Data Models
• Data Modeling
• Data Storage Systems
• Information Systems
• NoSQL

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