Relational model overview

Introduction to SQL — What is SQL? — History and standards (SQL-92, SQL:2011) — Popular RDBMS: MySQL, PostgreSQL, SQLite, SQL Server — SQL syntax and structure Database Basics — What is a database? — Tables, rows, columns — Primary key and foreign key — Relational model overview Creating and Managing Databases — CREATE DATABASE — USE, DROP DATABASE — Database naming conventions Creating and Managing Tables — CREATE TABLE syntax — Data types (INT, VARCHAR, DATE, etc.) — Constraints (NOT NULL, UNIQUE, DEFAULT) — DROP and ALTER TABLE Inserting Data — INSERT INTO syntax — Inserting single and multiple rows — Using DEFAULT values Querying Data (SELECT) — SELECT basics — Filtering with WHERE — Sorting with ORDER BY — DISTINCT keyword — LIMIT and OFFSET Filtering Data — Comparison operators (=, <>, >, etc.) — Logical operators (AND, OR, NOT) — BETWEEN, IN, LIKE — IS NULL / IS NOT NULL Updating and Deleting Data — UPDATE syntax — DELETE syntax — WHERE clause best practices — TRUNCATE vs DELETE Joins in SQL — INNER JOIN — LEFT JOIN — RIGHT JOIN — FULL OUTER JOIN — Self join and cross join Aggregate Functions — COUNT(), SUM(), AVG(), MIN(), MAX() — GROUP BY and HAVING — Filtering grouped data Subqueries — Subqueries in SELECT, WHERE, FROM — Correlated vs non-correlated subqueries Set Operations — UNION vs UNION ALL — INTERSECT and EXCEPT (if supported) Indexes — What is an index? — CREATE INDEX syntax — Unique index — Performance considerations Constraints and Keys — PRIMARY KEY — FOREIGN KEY — CHECK, DEFAULT — ON DELETE / ON UPDATE CASCADE Views — CREATE VIEW syntax — Updating data through views — Dropping views Stored Procedures — What is a stored procedure? — CREATE PROCEDURE — IN, OUT, INOUT parameters — Calling procedures Functions — User-defined functions (UDFs) — Differences from procedures — RETURN values and syntax Triggers — CREATE TRIGGER syntax — BEFORE / AFTER INSERT, UPDATE, DELETE — Use cases and examples Transactions and ACID — BEGIN, COMMIT, ROLLBACK — SAVEPOINT — Understanding ACID properties User and Permission Management — Creating users — GRANT and REVOKE privileges — Roles and security best practices Normalization and Database Design — 1NF, 2NF, 3NF — Denormalization — Designing efficient schemas Working with Dates and Time — DATE, TIME, DATETIME — DATE functions (NOW(), CURDATE(), DATEDIFF()) Common Built-in Functions — String functions (CONCAT, SUBSTRING, REPLACE) — Math functions (ROUND, FLOOR, CEIL) — Date functions (NOW, DATE_ADD, etc.) Performance Tuning — Query optimization — Using EXPLAIN — Reducing slow queries Real-World Projects — Student/course database — E-commerce schema — Blog or CMS backend — Library/book management system

Relational model overview

Understand Relational model overview in SQL for effective database querying and management.

Relational Model Overview

The Relational Model is a way to structure and organize data using relations (tables). It was proposed by Dr. E.F. Codd in 1970 and forms the theoretical foundation of relational databases.

In the relational model, data is represented as tuples (rows) grouped into relations (tables), with each relation having a unique name.

Key Concepts of the Relational Model

  • Relation (Table): A named collection of rows and columns.
  • Tuple (Row): A single record in a table.
  • Attribute (Column): A named field representing a data property.
  • Domain: The set of allowed values for a given attribute.
  • Primary Key: A unique identifier for each tuple.
  • Foreign Key: An attribute that links one relation to another.
  • Schema: The structure of the database (tables, attributes, relationships).

Example Relational Schema

Below is a simple relational model with two related tables:

Students
student_id (PK) name
1Amit
2Priya
Enrollments
enroll_id (PK) student_id (FK) course
1011Math
1022Science

In this example:

  • student_id is a Primary Key in Students.
  • student_id in Enrollments is a Foreign Key, referencing Students.

Advantages of the Relational Model

  • Simple and logical structure (tables).
  • Data integrity through keys and constraints.
  • Easily queried using SQL.
  • Supports relationships across multiple tables.
  • Flexible schema and normalization support.
Full Stack Development Course