Fundamentals of a Relational Database

Topics: Relational model, Database normalization, Data modeling Pages: 20 (7444 words) Published: April 11, 2013
Fundamentals of Relational Database Design
By Paul Litwin
This paper was part of a presentation at a Microsoft TechEd conference in the mid-1990s. It was adapted from Microsoft Access 2 Developer's Handbook, Sybex 1994, by Ken Getz, Paul Litwin and Greg Reddick. Reprinted with permission of the publisher. While the paper uses Microsoft Access (version 2) for the examples, the vast majority of the discussion applies to any database and holds up pretty well over 11 years after it was written. Overview

Database design theory is a topic that many people avoid learning for lack of time. Many others attempt to learn it, but give up because of the dry, academic treatment it is usually given by most authors and teachers. But if creating databases is part of your job, then you're treading on thin ice if you don't have a good solid understanding of relational database design theory. This article begins with an introduction to relational database design theory, including a discussion of keys, relationships, integrity rules, and the often-dreaded "Normal Forms." Following the theory, I present a practical step-by-step approach to good database design. The Relational Model

The relational database model was conceived by E. F. Codd in 1969, then a researcher at IBM. The model is based on branches of mathematics called set theory and predicate logic. The basic idea behind the relational model is that a database consists of a series of unordered tables (or relations) that can be manipulated using non-procedural operations that return tables. This model was in vast contrast to the more traditional database theories of the time that were much more complicated, less flexible and dependent on the physical storage methods of the data. Note: It is commonly thought that the word relational in the relational model comes from the fact that you relate together tables in a relational database. Although this is a convenient way to think of the term, it's not accurate. Instead, the word relational has its roots in the terminology that Codd used to define the relational model. The table in Codd's writings was actually referred to as a relation (a related set of information). In fact, Codd (and other relational database theorists) use the terms relations, attributes and tuples where most of us use the more common terms tables, columns and rows, respectively (or the more physical—and thus less preferable for discussions of database design theory—files, fields and records). The relational model can be applied to both databases and database management systems (DBMS) themselves. The relational fidelity of database programs can be compared using Codd's 12 rules (since Codd's seminal paper on the relational model, the number of rules has been expanded to 300) for determining how DBMS products conform to the relational model. When compared with other database management programs, Microsoft Access fares quite well in terms of relational fidelity. Still, it has a long way to go before it meets all twelve rules completely. Fortunately, you don't have to wait until Microsoft Access is perfect in a relational sense before you can benefit from the relational model. The relational model can also be applied to the design of databases, which is the subject of the remainder of this article. Relational Database Design

When designing a database, you have to make decisions regarding how best to take some system in the real world and model it in a database. This consists of deciding which tables to create, what columns they will contain, as well as the relationships between the tables. While it would be nice if this process was totally intuitive and obvious, or even better automated, this is simply not the case. A well-designed database takes time and effort to conceive, build and refine. The benefits of a database that has been designed according to the relational model are numerous. Some of them are: * Data entry, updates and deletions will be efficient.

* Data...
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