Integrity constraints are rules or conditions defined on the data in a database that ensure the accuracy, consistency, and validity of the data. They are used to enforce data integrity, preventing the database from entering inconsistent or incorrect data. Integrity constraints define the relationships between tables and enforce business rules or domain requirements on the data.
Here are some commonly used integrity constraints in database systems:
- Primary Key Constraint: This constraint ensures that each row in a table is uniquely identified. It specifies that a column or a combination of columns in a table must contain unique and non-null values.
- Foreign Key Constraint: This constraint establishes a relationship between two tables. It ensures that the values in a column (foreign key) of one table match the values in the primary key column of another table (referenced key). It helps maintain referential integrity and enforces data consistency between related tables.
- Unique Constraint: This constraint ensures that the values in a column or a combination of columns are unique across the table. It prevents duplicate values from being inserted or updated in the specified column(s).
- Not Null Constraint: This constraint specifies that a column cannot contain null values. It ensures that the required data is always present in the specified column.
- Check Constraint: This constraint defines a condition that must be satisfied for the data in a column. It allows you to define custom rules to restrict the values that can be inserted or updated in the column.
- Domain Constraint: This constraint specifies the valid set of values for a column based on its data type. It ensures that only appropriate values are entered in the column.
By applying these integrity constraints, database management systems can maintain the consistency and accuracy of the data stored in the database. Violation of these constraints typically results in an error and prevents the insertion or modification of data that would violate the defined rules.
Types of Integrity Constraint:
There are several types of integrity constraints that are commonly used in database systems. Here are the main types:
- Entity Integrity Constraint: This constraint ensures the uniqueness and non-nullability of the primary key in a table. It guarantees that each row in a table is uniquely identified and that the primary key value is not null.
- Referential Integrity Constraint: This constraint maintains the consistency and accuracy of the relationships between tables. It ensures that values in a foreign key column of a table match the values in the primary key column of another table. It prevents orphaned records by enforcing the existence of related records.
- Domain Integrity Constraint: This constraint defines the permissible values for a column based on its data type and domain. It ensures that only valid and appropriate values are stored in the database. For example, a domain integrity constraint on a column representing a person’s age may specify that the age must be a positive integer.
- Key Integrity Constraint: This constraint ensures the uniqueness of a candidate key in a table, which may or may not be the primary key. It guarantees that the values in the specified column(s) are unique and that there are no duplicate key values.
- Check Integrity Constraint: This constraint defines a condition or an expression that must evaluate to true for the data in a column or a table. It allows you to specify custom rules or conditions that the data must adhere to. For example, a check constraint may be used to enforce a condition that a product’s price must be greater than zero.
- Semantic Integrity Constraint: This constraint enforces domain-specific rules or business rules on the data. It ensures that the data in the database conforms to the semantics and constraints of the real-world application domain. These constraints are often implemented using a combination of domain-specific rules and custom logic.
These integrity constraints work together to maintain the integrity and consistency of the data in a database, ensuring that it accurately represents the real-world information it is intended to store.