Relational Data Model

Feature of Relational Data Model

  1. We can check relationship between data with the primary key and the foreign key referring to it.

  2. Relational Data Model is typically SQL and can represent 1:1, 1:N, and N:M relationships.

  • One customer can orders multiple. This is 1:N

  • Order sheet is linked to one order number. This is 1:1


Field and Column

The smallest logical unit that makes up a database can be considered a 'Field' or 'Column'. A field is the smallest unit of a database table and each field contains only one type of data.

Domain

In the context of databases, a 'domain' refers to the set of possible values that a field (or attribute, or column) can hold. It defines the data type and constraints for the data stored in the field.

For example, a field named "Gender" in a database might have a domain specifying that the value should be either "Male" or "Female". This means that the field "Gender" can only contain either "Male" or "Female", and any other input would not be accepted.

In other words, the domain provides the range of permissible values that a field can contain, thereby ensuring the integrity and accuracy of the data in the database.

Relation

When discussing the characteristics of a relation (or relational table) in a relational database, a few key points often come to the forefront.

  1. Column Order is Not Significant: In a relational database model, the order in which the columns appear in the table is not significant. This is because data is accessed based on column name, not the position of the column in the table. You can rearrange the order of the columns without affecting the integrity or functionality of the database.

  2. Atomic Values: Relations in a database should store atomic (indivisible) values. This principle is part of the First Normal Form (1NF), a fundamental aspect of database normalization. In essence, this means that each cell in a table should contain only one value, rather than a set of values or complex structures. This property makes the data easier to understand, manipulate, and helps prevent duplication and inconsistencies.

These characteristics are part of the foundation of relational database design, and are crucial for ensuring efficient and accurate data management.