RDBMS vs. OODBMS: Comparing Database Management Systems

Introduction

The proliferation of database technologies, systems, and data structures continues to be driven by the needs organizations have for making more efficient and economical use of their data. Web-based applications that have increased in speed and security have acted as a catalyst for database growth, and will continue to do so as programming languages become more agile and flexible in design. Continual improvements in Relational Database Management Systems (RDBMS) and Object-Oriented Database Management Systems (OODBMS) are also leading to the development of enterprise systems that can scale across a company's entire value chain. The intent of this paper is to evaluate the purpose, development, and functions of RDBMS and OODBMS, in addition to comparing the advantages and disadvantages of these two dominant types of databases.

Fundamentals of Relational Database Management Systems

Of the two types of databases compared in this analysis, RDBMS is far more prevalently used today, as many Fortune 500 companies have standardized on it for the last three decades. An RDBMS is more agile and efficient in managing transaction-specific requests and forms the foundation of Enterprise Resource Planning (ERP), distributed order management, and Supply Chain Management (SCM) enterprise applications (Evermann & Wand, 2009). RDBMS-based platforms are also purpose-built to manage transaction-centric data and perform more effectively than OODBMS systems on these tasks. As a result, they are the database architecture of choice for the development and continual enhancement of transaction-centric enterprise systems (Connolly & Begg, 2006).

Another aspect of the RDBMS design that enables this architecture to be more effective at enterprise-wide tasks is the table- and array-based approach to storing and managing data. Enterprise system developers have found that using complex or multidimensional arrays for storing data — so they can be used for role-based usage requirements — significantly improves both the usability and performance of ERP systems, for example. This role-based approach to enterprise system use is based on providing database queries from tables and predefined record and data structures that are selectively updated based on department, division, and role-based data structure definitions.

The fundamental structure of an RDBMS is based on record- and row-based data that comprise a record. Each element or item in a record has a unique logical address in the data table, which makes the development of data structures highly efficient. As each row in an RDBMS is considered a record, a key field is used that defines the identity, logical location, and attributes of the table the record is part of. This key identifier field — which has a variety of names depending on the specific type of RDBMS used — is the pivotal element in the RDBMS, as it is used for linking one record, table, or database to another. This key identifier field also enables the linking of tables together and assists in the formation of data structures.

With the foundation of a database designed, the query languages used to traverse tables, create reports, and define entire applications based on their architectures become critical. The majority of RDBMS systems use a structured query language — often referred to as Standard Query Language (SQL). SQL is the language used for defining and running reports, often interlinking data from a variety of RDBMS systems and data structures.

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