Relational Database Model

The Relational Model Concepts:

The foundation of the relational database model rests upon fundamental concepts crucial for understanding its structure and functioning.

• Relations/Tables: Relations in a database are akin to tables, comprising rows (tuples) and columns (attributes). Each row signifies a unique entity instance, while each column represents an attribute of that entity.

• Attributes: Attributes are the properties or characteristics of entities stored within the tables. Each attribute is defined by a name and domain, specifying the type of values it can hold.

• Primary Key: A primary key serves as a distinct identifier for a row within a table. It upholds data integrity and facilitates inter-table relationships by ensuring uniqueness.

• Foreign Key: Existing within a table, a foreign key refers to the primary key of another table. It establishes connections between tables, fostering relational links.

• Integrity Constraints: These rules safeguard the accuracy and consistency of data within a database. They encompass primary key constraints, foreign key constraints, unique constraints, and check constraints.

The Relational Constraints and Relational Database Schemas:

A relational database schema comprises rules governing the database structure, encompassing tables, columns, relationships, and constraints. Constraints play a pivotal role in maintaining data integrity and averting inconsistencies:

• Primary Key Constraint: Enforces uniqueness for each row by designating one or more columns as the primary key.

• Foreign Key Constraint: Defines a column in one table as a reference to the primary key in another, establishing relationships.

• Unique Constraint: Ensures the uniqueness of values in columns or combinations of columns.

• Check Constraint: Validates that column values adhere to specific conditions.

The Relational Operations:

The relational database model facilitates a spectrum of operations essential for data manipulation:

• Select: Retrieves data from one or more tables based on specified conditions.

• Project: Extracts a subset of columns from a table.

• Join: Merges data from multiple tables using common columns.

• Union: Combines data from different tables into a single table.

• Intersection: Fetches common data between two tables.

• Difference: Retrieves data present in one table but absent in another.

• Aggregate: Performs calculations (sum, count, average, maximum, minimum) on table data.

These operations can be intricately combined to execute sophisticated queries and manipulate data within a relational database, allowing for versatile data handling and retrieval.