This paper provides an overview of database systems as used in modern enterprise environments. It examines how relational database management systems (RDBMS) and object-oriented database management systems (OODBMS) differ in architecture, performance characteristics, and appropriate use cases. The paper covers fundamental database concepts such as schema, subschema, and data attributes, then focuses on relational databases — including products from Microsoft, Oracle, and IBM — and their role in transaction processing, supply chain management, ERP, and CRM systems. IBM's Service Management program is highlighted as a practical case study in RDBMS integration with legacy platforms.
The pervasive adoption of databases for aggregating, analyzing, parsing, reporting, and storing data continues to increase exponentially over time as the information needs of companies grow. The foundation of nearly every enterprise-wide system and computing platform includes integration with databases of many types, from object-oriented to relational (Lungu, Velicanu, & Botha, 2009). Every Enterprise Resource Planning (ERP) system today relies on databases for product management, pricing, costing, production scheduling, service coordination, and manufacturing execution task coordination (Bremer & Carey, 1987).
Databases have become an essential component of every enterprise system in use today, from coordinating supply chains and sourcing to tracking customer activity and sales through Customer Relationship Management (CRM) systems (Madduri, Shi, Baker, & Ayachitula, 2007). Object-oriented databases are also pervasively used in Computer-Aided Drawing (CAD) applications, given their speed and accuracy in managing geographic and graphic primitives (Chu, 1995).
All databases share a series of common features, functional areas, and approaches to data modeling. In addition, all have the ability to integrate with other databases in either batch or real-time mode (He, 1998). All databases also support a series of database schema and advanced taxonomy definitions, which are entirely dependent on the foundational elements of the underlying architecture.
Object-oriented databases use orthogonal objects that carry their own functional and taxonomy definitions (Hansen, 1995). Relational databases (RDBMS) rely on a more schema-based approach to define the data models used for completing analysis, reporting, and ensuring a high degree of integration reliability and security (Hansen, 1995). All databases rely on schema and subschema, and within these constructs, the ability to define data attributes. Of the two dominant types of databases — OODBMS and RDBMS — the latter performs best for high-volume transaction processing (Hooper & Page, 1996), while OODBMS is best for managing unstructured content and the rapid analysis and classification of object-based content (Newing, 1997).
"RDBMS dominance, SQL platforms, and IBM case study"
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