The relational data model was introduced by E. F. Codd in 1970. Currently, it is the most widely used data model.
The relational model has provided the basis for:
The relational data model describes the world as “a collection of inter-related relations (or tables).”
A relation, also known as a table or file, is a subset of the Cartesian product of a list of domains characterized by a name. And within a table, each row represents a group of related data values. A row, or record, is also known as a tuple. The columns in a table is a field and is also referred to as an attribute. You can also think of it this way: an attribute is used to define the record and a record contains a set of attributes.
The steps below outline the logic between a relation and its domains.
A database is composed of multiple tables and each table holds the data. Figure 7.1 shows a database that contains three tables.
A database stores pieces of information or facts in an organized way. Understanding how to use and get the most out of databases requires us to understand that method of organization.
The principal storage units are called columns or fields or attributes. These house the basic components of data into which your content can be broken down. When deciding which fields to create, you need to think generically about your information, for example, drawing out the common components of the information that you will store in the database and avoiding the specifics that distinguish one item from another.
Look at the example of an ID card in Figure 7.2 to see the relationship between fields and their data.
A domain is the original sets of atomic values used to model data. By atomic value, we mean that each value in the domain is indivisible as far as the relational model is concerned. For example:
In summary, a domain is a set of acceptable values that a column is allowed to contain. This is based on various properties and the data type for the column. We will discuss data types in another chapter.
Just as the content of any one document or item needs to be broken down into its constituent bits of data for storage in the fields, the link between them also needs to be available so that they can be reconstituted into their whole form. Records allow us to do this. Records contain fields that are related, such as a customer or an employee. As noted earlier, a tuple is another term used for record.
Records and fields form the basis of all databases. A simple table gives us the clearest picture of how records and fields work together in a database storage project.
The simple table example in Figure 7.3 shows us how fields can hold a range of different sorts of data. This one has:
You can command the database to sift through its data and organize it in a particular way. For example, you can request that a selection of records be limited by date: 1. all before a given date, 2. all after a given date or 3. all between two given dates. Similarly, you can choose to have records sorted by date. Because the field, or record, containing the data is set up as a Date field, the database reads the information in the Date field not just as numbers separated by slashes, but rather, as dates that must be ordered according to a calendar system.
The degree is the number of attributes in a table. In our example in Figure 7.3, the degree is 4.
atomic value: each value in the domain is indivisible as far as the relational model is concernedattribute: principle storage unit in a database
column: see attribute
degree: number of attributes in a table
domain: the original sets of atomic values used to model data; a set of acceptable values that a column is allowed to contain
field: see attribute
file:see relation
record: contains fields that are related; see tuple
relation: a subset of the Cartesian product of a list of domains characterized by a name; the technical term for table or file
row: see tuple
structured query language (SQL): the standard database access language
table:see relation
tuple: a technical term for row or record
Several of the terms used in this chapter are synonymous. In addition to the Key Terms above, please refer to Table 7.1 below. The terms in the Alternative 1 column are most commonly used.
Use Table 7.2 to answer questions 1-4.
This chapter of Database Design (including images, except as otherwise noted) is a derivative copy of Relational Design Theory by Nguyen Kim Anh licensed under Creative Commons Attribution License 3.0 license
The following material was written by Adrienne Watt:
Database Design - 2nd Edition Copyright © 2014 by Adrienne Watt is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.
