Constraints restrict data values from "summary" of SQL and Relational Theory by C. Date
The concept of constraints in databases is a crucial one. Constraints play a significant role in ensuring the integrity of the data stored in a relational database. One essential function of constraints is to restrict the values that can be placed in certain columns of a table. This restriction helps maintain the consistency and accuracy of the data within the database. By applying constraints to specific columns, database designers can enforce rules that dictate the acceptable values for those columns. For example, a constraint may specify that a column can only contain numeric values between a certain range, or that a column must contain a unique value for each row in the table. These rules help prevent the insertion of incorrect or inconsistent data into the database. Constraints can take various forms, such as NOT NULL constraints, UNIQUE constraints, PRIMARY KEY constraints, FOREIGN KEY constraints, and CHECK constraints. Each type of constraint serves a specific purpose in defining the permissible values for a column. NOT NULL constraints, for instance, ensure that a column cannot contain null values, while UNIQUE constraints enforce the uniqueness of values in a column. By imposing constraints on data values, database designers can establish a set of rules that govern the behavior of the database. These rules help maintain data integrity and consistency, preventing data anomalies that could compromise the reliability of the database. Constraints also play a vital role in enforcing the relationships between tables, ensuring that referential integrity is preserved throughout the database.- Constraints are a fundamental aspect of database design and management. They provide a mechanism for enforcing data integrity and consistency, helping to maintain the quality and reliability of the data stored in a relational database. By restricting data values based on predefined rules, constraints help ensure that the database operates effectively and accurately in accordance with the intended data model.
