Introduction to Relational Databases

A relational database is a type of database that stores information in tables made up of rows and columns. It is called “relational” because tables can be related to each other using keys.

This model was introduced by Edgar F. Codd in the 1970s and has become the foundation of most business and enterprise data systems.

1. What Is a Relational Database?

A relational database:

Organizes data in tables (like spreadsheets)

Uses relationships between tables to connect data

Ensures data is consistent, accurate, and structured

Allows powerful queries using SQL (Structured Query Language)

Examples of relational database systems:

MySQL

PostgreSQL

Oracle Database

Microsoft SQL Server

SQLite

2. Key Concepts in Relational Databases

2.1 Tables

A table represents an entity—like Customers, Orders, Employees, or Products.

Example table: Customers

CustomerID Name Email

1 Alice Lee alice@example.com

2 Bob Chen bob@example.com

2.2 Rows and Columns

A row represents a single record

A column represents a field (attribute) of that record

For example, in a Customers table:

Each customer = 1 row

Name, Email, CustomerID = columns

2.3 Primary Keys

A primary key uniquely identifies each row.

Examples:

CustomerID in Customers

OrderID in Orders

Primary keys must be:

Unique

Not null

2.4 Foreign Keys

A foreign key connects two tables by referencing the primary key of another table.

Example:

Orders table contains:

OrderID CustomerID Amount

Here, CustomerID is a foreign key pointing to Customers.CustomerID.

This creates a relationship:

One customer → many orders

2.5 Relationships

There are three main types:

1. One-to-One

One record corresponds to exactly one record.

Example:

User ↔ UserProfile

2. One-to-Many (most common)

One record corresponds to many records.

Example:

Customer → Orders

3. Many-to-Many

Requires a junction table.

Example:

Students ↔ Courses

Junction table: StudentCourses

3. SQL: How We Interact with Relational Databases

SQL (Structured Query Language) is the standard language used to store, update, and retrieve data.

Common SQL operations

SELECT – read data

SELECT * FROM Customers;

INSERT – add data

INSERT INTO Customers (Name, Email)

VALUES ('Alice', 'alice@example.com');

UPDATE – modify data

UPDATE Customers

SET Email = 'newalice@example.com'

WHERE CustomerID = 1;

DELETE – remove data

DELETE FROM Customers

WHERE CustomerID = 1;

4. Why Use a Relational Database?

4.1 Structured and Organized

Great for applications where data has clear structure.

4.2 Data Integrity

Constraints ensure:

No duplicate users

No missing required fields

Valid relationships

4.3 Transactions

Relational databases support ACID:

Atomicity

Consistency

Isolation

Durability

Critical for banking, ordering systems, inventory, etc.

4.4 Powerful Querying

SQL can:

Join tables

Filter and sort data

Aggregate (sum, count, average)

Analyze large datasets

4.5 Mature and Reliable

Relational databases have been used for decades and are trusted in:

Finance

Healthcare

E-commerce

Government

Enterprise applications

5. Common Use Cases

Relational databases are ideal for:

E-commerce websites

Banking systems

Inventory management

ERP systems

CRM systems

Reservation platforms

Data warehousing (with extensions)

Where data accuracy and consistency matter, RDBMS systems excel.

6. Limitations of Relational Databases

Although powerful, they have some limitations:

Not ideal for highly unstructured data

Harder to scale horizontally compared to NoSQL

Schemas are rigid—changing structure requires planning

May struggle with massive real-time workloads

For these cases, NoSQL databases (like MongoDB, Cassandra) or cloud-native stores may work better.

7. Summary

A relational database is a structured system that stores data in tables connected by relationships. It ensures consistency, reliability, and powerful querying through SQL.

Key points:

Data stored in tables, rows, and columns

Primary keys and foreign keys define relationships

Supports ACID transactions

Ideal for structured business data

Used everywhere from banking to e-commerce

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