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Creating Your First Database and Table

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Table of Contents

  1. Introduction
  2. What is a Database in SQL?
  3. What is a Table in SQL?
  4. Syntax of CREATE DATABASE
  5. Creating a Database in SQLite
  6. Creating a Database in MySQL
  7. Creating a Database in PostgreSQL
  8. Syntax of CREATE TABLE
  9. Choosing Good Column Names
  10. Understanding Data Types
  11. Defining Primary Keys
  12. Adding NOT NULL and UNIQUE Constraints
  13. Creating a Basic Table Example
  14. Inserting First Row of Data
  15. Verifying Table Creation with SELECT
  16. Dropping and Re-Creating Tables
  17. Creating Tables with Foreign Keys
  18. Best Practices for Table Design
  19. Common Mistakes to Avoid
  20. Summary and What’s Next

1. Introduction

Now that you’ve set up your SQL environment, it’s time to create your first database and table. This module will guide you through syntax, conventions, and best practices using SQLite, MySQL, and PostgreSQL.


2. What is a Database in SQL?

A database is a container that holds all your tables, relationships, and metadata. Think of it as a folder on your system where all structured data for a project lives.


3. What is a Table in SQL?

A table is where actual data resides inside the database. Each table consists of columns (fields) and rows (records), similar to a spreadsheet.


4. Syntax of CREATE DATABASE

Basic SQL syntax:

CREATE DATABASE my_first_db;

Use this statement in MySQL or PostgreSQL. SQLite creates the database as a file, so it doesn’t need this command explicitly.


5. Creating a Database in SQLite

You create a new database by simply referencing a new file:

sqlite3 my_first_db.sqlite

You’re now inside the SQLite shell with a new database file created.


6. Creating a Database in MySQL

CREATE DATABASE my_first_db;
USE my_first_db;

MySQL requires you to switch to the newly created database using the USE command.


7. Creating a Database in PostgreSQL

CREATE DATABASE my_first_db;
\c my_first_db -- switch to database

PostgreSQL also allows database creation using pgAdmin’s GUI interface.


8. Syntax of CREATE TABLE

CREATE TABLE table_name (
column1 datatype constraint,
column2 datatype constraint,
...
);

Example:

CREATE TABLE users (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
email TEXT UNIQUE
);

9. Choosing Good Column Names

  • Use snake_case: first_name, created_at
  • Be descriptive: use email instead of e
  • Avoid SQL keywords like order, group

10. Understanding Data Types

Data TypeDescriptionCommon In
INTEGERWhole numbersAll
TEXTVariable-length stringSQLite
VARCHAR(n)String with max length nMySQL, PG
DATEDate valuesAll
BOOLEANTrue/FalsePG, MySQL
FLOAT/DECIMALDecimal numbersAll

11. Defining Primary Keys

Primary keys uniquely identify a record. Usually assigned to id columns.

id INTEGER PRIMARY KEY

In MySQL:

id INT AUTO_INCREMENT PRIMARY KEY

In PostgreSQL:

id SERIAL PRIMARY KEY

12. Adding NOT NULL and UNIQUE Constraints

Constraints enforce data integrity:

name TEXT NOT NULL,
email TEXT UNIQUE
  • NOT NULL: Prevents null values
  • UNIQUE: Prevents duplicate values

13. Creating a Basic Table Example

CREATE TABLE users (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
email TEXT UNIQUE,
age INTEGER,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
  • AUTOINCREMENT (SQLite)
  • DEFAULT CURRENT_TIMESTAMP sets automatic timestamp

14. Inserting First Row of Data

INSERT INTO users (name, email, age)
VALUES ('Anjali', '[email protected]', 24);

You can also insert multiple rows at once:

INSERT INTO users (name, email, age) VALUES
('Ravi', '[email protected]', 30),
('Neha', '[email protected]', 28);

15. Verifying Table Creation with SELECT

SELECT * FROM users;

This displays all columns and rows in the users table.


16. Dropping and Re-Creating Tables

To drop a table:

DROP TABLE users;

To recreate, just run the CREATE TABLE statement again. This is helpful during development.


17. Creating Tables with Foreign Keys

Foreign keys maintain relationships between tables.

Example:

CREATE TABLE orders (
order_id INTEGER PRIMARY KEY,
user_id INTEGER,
order_date DATE,
FOREIGN KEY (user_id) REFERENCES users(id)
);

18. Best Practices for Table Design

  • Use id as the primary key for every table
  • Use lowercase names and snake_case formatting
  • Avoid NULL values unless they’re meaningful
  • Index frequently searched columns
  • Document each table with inline comments

19. Common Mistakes to Avoid

  • Forgetting to define a primary key
  • Using ambiguous column names like data or value
  • Using too general data types (e.g., TEXT for dates)
  • Not testing with actual sample inserts
  • Forgetting to check constraints during inserts

20. Summary and What’s Next

You’ve now created your first database and table across SQLite, MySQL, and PostgreSQL environments. You learned the importance of syntax, constraints, column naming, and how to insert your first records.

Setting Up Your SQL Environment (SQLite, MySQL, PostgreSQL)

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sql course

Table of Contents

  1. Introduction
  2. Choosing the Right SQL Database for Learning
  3. Overview of SQLite
  4. Installing SQLite
  5. Using SQLite Command Line Interface
  6. GUI Tools for SQLite
  7. Overview of MySQL
  8. Installing MySQL on Windows/macOS/Linux
  9. Accessing MySQL via Command Line
  10. GUI Tools for MySQL (MySQL Workbench)
  11. Overview of PostgreSQL
  12. Installing PostgreSQL on Windows/macOS/Linux
  13. Accessing PostgreSQL via psql
  14. GUI Tools for PostgreSQL (pgAdmin)
  15. Creating Your First Database
  16. Creating Tables Using SQL
  17. Importing Sample Data
  18. Running Your First Query
  19. Tips for Managing Local SQL Environments
  20. Summary and What’s Next

1. Introduction

Before you can write SQL queries, you need a running database environment. In this module, we’ll guide you through setting up three of the most popular relational database management systems: SQLite, MySQL, and PostgreSQL. Each one is free and widely used across different industries.


2. Choosing the Right SQL Database for Learning

DatabaseBest ForFeatures
SQLiteBeginners, mobile appsLightweight, no server needed
MySQLWeb development, CMS appsWidely used, fast, reliable
PostgreSQLEnterprise apps, analyticsOpen-source, advanced features

SQLite is ideal for quick experimentation. MySQL is best if you’re interested in web apps like WordPress. PostgreSQL is perfect for those exploring advanced SQL features.


3. Overview of SQLite

SQLite is a self-contained, serverless, and zero-configuration database engine. It’s widely used in mobile applications, browsers, and embedded systems.


4. Installing SQLite

Windows/macOS/Linux:

  1. Go to: https://www.sqlite.org/download.html
  2. Download the precompiled binaries for your platform.
  3. Extract and add to system PATH.

To test:

sqlite3 --version

5. Using SQLite Command Line Interface

Start a new database:

sqlite3 mydatabase.db

Example:

CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT, email TEXT);
INSERT INTO users (name, email) VALUES ('Ravi', '[email protected]');
SELECT * FROM users;

Exit with .exit.


6. GUI Tools for SQLite

If you’re not comfortable with the terminal, try:

These tools provide drag-and-drop table creation, SQL editing, and data visualization.


7. Overview of MySQL

MySQL is a high-performance open-source RDBMS maintained by Oracle. It’s the backbone of many content management systems and supports large-scale applications.


8. Installing MySQL on Windows/macOS/Linux

Windows:

  1. Download the MySQL Installer from https://dev.mysql.com/downloads/installer/
  2. Choose “Developer Default”
  3. Set a root password and remember it

macOS:

brew install mysql
brew services start mysql

Linux (Ubuntu):

sudo apt update
sudo apt install mysql-server
sudo mysql_secure_installation

9. Accessing MySQL via Command Line

Start the MySQL shell:

mysql -u root -p

Create and use a database:

CREATE DATABASE testdb;
USE testdb;
CREATE TABLE demo (id INT PRIMARY KEY, name VARCHAR(100));

10. GUI Tools for MySQL (MySQL Workbench)

Download from: https://dev.mysql.com/downloads/workbench/

Features:

  • SQL Editor
  • ER Diagrams
  • Server Configuration
  • User and Privilege Management

11. Overview of PostgreSQL

PostgreSQL is a powerful, open-source object-relational database. Known for standards compliance and extensibility, it is popular in financial, GIS, and analytics-heavy systems.


12. Installing PostgreSQL on Windows/macOS/Linux

Windows/macOS:

Use the installer from: https://www.postgresql.org/download/

During setup:

  • Choose components (pgAdmin, StackBuilder)
  • Set password for superuser postgres

Linux (Ubuntu):

sudo apt update
sudo apt install postgresql postgresql-contrib

13. Accessing PostgreSQL via psql

Connect to the shell:

sudo -u postgres psql

Create and use a database:

CREATE DATABASE mydb;
\c mydb
CREATE TABLE users (id SERIAL PRIMARY KEY, name VARCHAR(100));

Exit with \q.


14. GUI Tools for PostgreSQL (pgAdmin)

pgAdmin is the official PostgreSQL GUI:

  • Visual query editor
  • Backup/restore tools
  • User management

Download from: https://www.pgadmin.org/download/


15. Creating Your First Database

In any of the three systems:

CREATE DATABASE testdb;

Use the database:

-- MySQL / PostgreSQL
USE testdb;

-- SQLite: done when file is opened

16. Creating Tables Using SQL

CREATE TABLE users (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
email TEXT UNIQUE
);

Syntax may vary slightly (e.g., AUTO_INCREMENT in MySQL, SERIAL in PostgreSQL).


17. Importing Sample Data

You can import CSV files using:

SQLite:

.mode csv
.import users.csv users

MySQL:

LOAD DATA INFILE '/path/users.csv'
INTO TABLE users
FIELDS TERMINATED BY ','
LINES TERMINATED BY '\n'
IGNORE 1 ROWS;

PostgreSQL:

COPY users(name, email)
FROM '/path/users.csv'
DELIMITER ','
CSV HEADER;

18. Running Your First Query

Try this after creating and inserting data:

SELECT * FROM users;
SELECT name FROM users WHERE email LIKE '%@gmail.com';

Use ORDER BY, LIMIT, and WHERE for richer queries.


19. Tips for Managing Local SQL Environments

  • Use GUI tools if CLI feels overwhelming
  • Always back up before major changes
  • Avoid using root/admin users in practice
  • Use version control for schema files (.sql)
  • Organize your queries and notes

20. Summary and What’s Next

In this module, you learned how to:

  • Set up SQLite, MySQL, and PostgreSQL
  • Use CLI and GUI tools for each system
  • Create databases, tables, and run queries

Whether you’re a beginner or intermediate developer, having at least one local SQL environment is essential for practice and learning.

Overview of SQL Syntax and Structure

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sql course

Table of Contents

  1. Introduction
  2. SQL Syntax: The Basics
  3. SQL Keywords and Case Sensitivity
  4. The Structure of a SQL Statement
  5. Understanding Clauses in SQL
  6. Writing Your First SQL Statement
  7. The SELECT Statement
  8. Using WHERE for Filtering
  9. ORDER BY for Sorting Results
  10. INSERT INTO: Adding New Records
  11. UPDATE: Modifying Existing Data
  12. DELETE: Removing Records
  13. Creating Tables with CREATE TABLE
  14. Altering Tables with ALTER TABLE
  15. Dropping Tables with DROP TABLE
  16. SQL Comments
  17. Common Mistakes in SQL Syntax
  18. Formatting and Readability Best Practices
  19. Example: Full CRUD Cycle in SQL
  20. Summary and Next Steps

1. Introduction

Structured Query Language (SQL) is a standardized language used to communicate with relational databases. Before diving into advanced queries or optimization techniques, it’s essential to understand the syntax and structure of SQL.

This module gives you a hands-on overview of SQL’s syntax and statement structure so you can confidently begin working with relational data.


2. SQL Syntax: The Basics

SQL statements are made up of:

  • Keywords (e.g., SELECT, FROM, WHERE)
  • Identifiers (e.g., table names, column names)
  • Expressions (e.g., age > 30)
  • Literals (e.g., ‘India’, 100)

Example:

sqlCopyEditSELECT name, age FROM users WHERE age > 30;

3. SQL Keywords and Case Sensitivity

SQL keywords are not case-sensitive, meaning the following are equivalent:

sqlCopyEditSELECT * FROM users;
select * from users;
SeLeCt * FrOm users;

However, for best practice and readability, it’s common to write:

  • Keywords in uppercase (SELECT, WHERE)
  • Table and column names in lowercase or snake_case

4. The Structure of a SQL Statement

A typical SQL statement follows this logical pattern:

sqlCopyEditSELECT columns
FROM table_name
WHERE condition
GROUP BY column
HAVING condition
ORDER BY column
LIMIT number;

Not all clauses are mandatory. The SELECT, FROM, and optional WHERE are the most commonly used.


5. Understanding Clauses in SQL

Here’s a breakdown of the most common SQL clauses:

ClausePurpose
SELECTChoose which columns to retrieve
FROMSpecify the table(s) to query from
WHEREFilter records based on a condition
GROUP BYAggregate data by specified columns
HAVINGFilter grouped records
ORDER BYSort the output
LIMITLimit the number of rows returned

6. Writing Your First SQL Statement

Example:

sqlCopyEditSELECT name, email
FROM customers
WHERE country = 'India'
ORDER BY name ASC;

This retrieves all customers from India and sorts them by name in ascending order.


7. The SELECT Statement

SELECT is used to retrieve data from a database.

sqlCopyEditSELECT * FROM products;
SELECT name, price FROM products;

Use * to select all columns or specify column names explicitly.


8. Using WHERE for Filtering

WHERE is used to apply conditions:

sqlCopyEditSELECT * FROM orders
WHERE status = 'pending' AND total > 500;

Operators you can use include: =, !=, <, >, <=, >=, BETWEEN, IN, LIKE, IS NULL


9. ORDER BY for Sorting Results

sqlCopyEditSELECT * FROM users
ORDER BY created_at DESC;

ASC for ascending (default), DESC for descending order.


10. INSERT INTO: Adding New Records

sqlCopyEditINSERT INTO users (name, email, age)
VALUES ('Anjali', '[email protected]', 24);

You can insert multiple records at once:

sqlCopyEditINSERT INTO users (name, age) 
VALUES ('Ravi', 22), ('Neha', 30);

11. UPDATE: Modifying Existing Data

sqlCopyEditUPDATE users
SET age = 26
WHERE name = 'Anjali';

Always use WHERE to avoid updating all rows unintentionally.


12. DELETE: Removing Records

sqlCopyEditDELETE FROM users
WHERE age < 18;

Use caution: without WHERE, all rows will be deleted.


13. Creating Tables with CREATE TABLE

sqlCopyEditCREATE TABLE users (
    id INT PRIMARY KEY AUTO_INCREMENT,
    name VARCHAR(100),
    email VARCHAR(100) UNIQUE,
    age INT,
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

Defines a table and its columns, data types, and constraints.


14. Altering Tables with ALTER TABLE

To add a column:

sqlCopyEditALTER TABLE users ADD phone_number VARCHAR(15);

To remove a column:

sqlCopyEditALTER TABLE users DROP COLUMN phone_number;

15. Dropping Tables with DROP TABLE

sqlCopyEditDROP TABLE users;

Use carefully—this removes the entire table and all its data.


16. SQL Comments

You can write comments in your SQL code using:

  • -- for single-line comments
  • /* ... */ for multi-line comments

Example:

sqlCopyEdit-- This is a comment
SELECT * FROM users; /* Get all users */

17. Common Mistakes in SQL Syntax

  • Missing semicolon (;)
  • Using incorrect column or table names
  • Forgetting WHERE in UPDATE or DELETE
  • Not matching value types (e.g., using string quotes around numbers)

18. Formatting and Readability Best Practices

  • Uppercase SQL keywords (SELECT, FROM, WHERE)
  • One clause per line for readability
  • Use indentation for nested queries
  • Avoid hard-coding sensitive data

Example:

sqlCopyEditSELECT id, name
FROM employees
WHERE department = 'HR'
ORDER BY name ASC;

19. Example: Full CRUD Cycle in SQL

sqlCopyEdit-- CREATE
CREATE TABLE tasks (
    id INT PRIMARY KEY AUTO_INCREMENT,
    title VARCHAR(255),
    status VARCHAR(50)
);

-- INSERT
INSERT INTO tasks (title, status)
VALUES ('Complete SQL module', 'pending');

-- READ
SELECT * FROM tasks;

-- UPDATE
UPDATE tasks SET status = 'completed' WHERE id = 1;

-- DELETE
DELETE FROM tasks WHERE id = 1;

20. Summary and Next Steps

In this module, you learned the foundational elements of SQL syntax and structure. From writing basic queries to understanding how to create, read, update, and delete records, you’ve laid the groundwork for deeper SQL learning.

SQL vs NoSQL: When to Use What

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sql course

Table of Contents

  1. Introduction to Data Storage Paradigms
  2. The Rise of SQL and NoSQL
  3. What is SQL?
  4. Key Characteristics of SQL Databases
  5. What is NoSQL?
  6. The Four Major Types of NoSQL Databases
  7. Schema: Rigid vs Flexible
  8. Query Language Differences
  9. Scaling Approaches: Vertical vs Horizontal
  10. Data Consistency Models: ACID vs BASE
  11. SQL Strengths: Why SQL Still Dominates
  12. NoSQL Strengths: Agile and Scalable
  13. SQL Limitations
  14. NoSQL Limitations
  15. Use Case Comparison: SQL vs NoSQL
  16. SQL vs NoSQL Performance Considerations
  17. Security and Compliance in SQL and NoSQL
  18. Real-World Examples of SQL and NoSQL Usage
  19. When to Use Both (Polyglot Persistence)
  20. Conclusion and Recommendation

1. Introduction to Data Storage Paradigms

In a data-driven world, the choice of database technology is a foundational decision in any software architecture. Whether you’re building an enterprise ERP or a mobile chat app, the way data is stored, queried, and maintained significantly impacts performance, cost, and scalability.


2. The Rise of SQL and NoSQL

Historically, SQL databases were the de facto standard. But with the explosion of unstructured data and the need for real-time performance at massive scale, NoSQL databases began gaining momentum. Each approach has its strengths and ideal use cases.


3. What is SQL?

SQL, or Structured Query Language, is used in Relational Database Management Systems (RDBMS). These databases store data in well-defined tables consisting of rows and columns.

Popular SQL databases include:

  • MySQL
  • PostgreSQL
  • SQLite
  • Oracle
  • Microsoft SQL Server

4. Key Characteristics of SQL Databases

  • Tabular Structure: Data is organized in relational tables.
  • Fixed Schema: Defined before data entry.
  • ACID Transactions: Ensures atomicity, consistency, isolation, and durability.
  • Powerful Query Language: SQL is standardized and expressive.
  • Data Integrity and Constraints: Enforce rules like unique keys, foreign keys, etc.

5. What is NoSQL?

NoSQL databases are non-relational, meaning they don’t use the strict tabular format of SQL systems. They are designed for scalability, flexibility, and speed, particularly when dealing with semi-structured or unstructured data.


6. The Four Major Types of NoSQL Databases

  1. Document Stores (e.g., MongoDB): Store JSON or BSON documents.
  2. Key-Value Stores (e.g., Redis): Store simple key-value pairs.
  3. Column-Family Stores (e.g., Apache Cassandra): Store data in columns rather than rows.
  4. Graph Databases (e.g., Neo4j): Store nodes and edges for relationship-intensive data.

7. Schema: Rigid vs Flexible

SQL uses a rigid schema, requiring all data to follow a defined format. Any changes need schema migrations.

NoSQL supports schema-less or dynamic schemas, where documents or entities can vary in structure — ideal for iterative development and heterogeneous data.


8. Query Language Differences

SQL databases use the SQL language, known for its expressiveness and power:

SELECT * FROM users WHERE age > 25;

NoSQL databases often use:

  • JSON-based query syntax (e.g., MongoDB)
  • RESTful APIs (e.g., Firebase)
  • Gremlin/Cypher for graph queries (e.g., Neo4j)

There’s no standard query language across NoSQL systems.


9. Scaling Approaches: Vertical vs Horizontal

SQL databases traditionally scale vertically — adding more CPU, RAM, or SSD to a single server.

NoSQL databases are built for horizontal scaling — spreading data across multiple servers (sharding), enabling massive data handling across distributed environments.


10. Data Consistency Models: ACID vs BASE

ModelSQL (Relational)NoSQL (Non-Relational)
ACIDStrong consistency, ideal for transactional data (e.g., banks)Harder to implement at scale
BASEEventually Consistent, Available, Soft State

NoSQL sacrifices immediate consistency for availability and performance.


11. SQL Strengths: Why SQL Still Dominates

  • Mature Ecosystem: Decades of development and optimization.
  • Complex Queries: Supports multi-table joins, subqueries, aggregations.
  • Strong Consistency: Essential for financial and transactional systems.
  • Standardization: SQL is widely taught and used.

12. NoSQL Strengths: Agile and Scalable

  • Schema Flexibility: Great for evolving applications and startups.
  • High Throughput: Handles massive concurrent reads/writes.
  • Distributed Architecture: Natural fit for cloud environments.
  • Optimized for Specific Workloads: Time-series, graph, and real-time analytics.

13. SQL Limitations

  • Rigid Schemas: Modifying structure can be costly.
  • Limited Scalability: Harder to distribute across nodes.
  • Performance Bottlenecks: Under massive concurrent operations.

14. NoSQL Limitations

  • Lack of Standardization: Every system has different APIs and rules.
  • Weaker Consistency Guarantees: Eventually consistent models can be problematic.
  • Limited Querying: Joins and aggregations are harder or unsupported.
  • Learning Curve: Different syntax and paradigms.

15. Use Case Comparison: SQL vs NoSQL

Application TypeSQL RecommendedNoSQL Recommended
Banking & Finance
IoT Data Ingestion
CMS / Blog Platforms✅ / ✅ (both work)
Social Networking
Inventory Management
Real-time Chat
E-Commerce✅ + NoSQL (hybrid)

16. SQL vs NoSQL Performance Considerations

  • SQL excels in read-heavy operations on normalized data with indexing.
  • NoSQL often outperforms in high-speed insert/update workloads with denormalized data.
  • Latency and throughput for NoSQL systems scale better horizontally under large user loads.

17. Security and Compliance in SQL and NoSQL

SQL databases have mature tools for:

  • Role-based access control
  • Encryption at rest and in transit
  • Compliance (HIPAA, GDPR, PCI-DSS)

NoSQL databases are catching up but often lack uniform support across all tools, especially in open-source variants.


18. Real-World Examples of SQL and NoSQL Usage

SQL Examples:

  • PostgreSQL for GitLab’s metadata
  • MySQL for WordPress
  • Oracle in traditional ERP systems

NoSQL Examples:

  • MongoDB for content-rich apps like Medium
  • Cassandra for Netflix data streaming
  • Redis for caching and leaderboard systems in gaming apps

19. When to Use Both (Polyglot Persistence)

Modern applications often use polyglot persistence — leveraging SQL for critical business logic and NoSQL for performance-critical or unstructured workloads.

Example architecture:

  • SQL for user authentication, payments, admin dashboards.
  • NoSQL for product catalogs, analytics, logging, or messaging systems.

This allows each system to do what it does best.


20. Conclusion and Recommendation

Choosing between SQL and NoSQL depends on your project’s nature:

NeedUse
Strong consistency, structured dataSQL
Flexibility, high volume, scalabilityNoSQL
Real-time features + structured dataBoth (hybrid)

SQL remains the best choice for transactional systems and well-structured data.
NoSQL shines when flexibility, distributed systems, and massive scalability are required.

Understanding the strengths, trade-offs, and use cases of each will help you make architecture decisions that are scalable, secure, and maintainable.

Understanding Relational Databases

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sql course

Table of Contents

  1. What is a Relational Database?
  2. History and Evolution
  3. Core Concepts of Relational Databases
    • Tables
    • Rows and Columns
    • Primary Keys
    • Foreign Keys
  4. Relationships Between Tables
  5. Advantages of Relational Databases
  6. Limitations of Relational Databases
  7. Example Schema: E-Commerce System
  8. Summary

1. What is a Relational Database?

A Relational Database is a type of database that stores data in structured formats using rows and columns. Each piece of data is stored in a table, and these tables can relate to one another through keys, which is where the term “relational” comes from.

Relational databases are the most widely used type of database, particularly when consistency, accuracy, and the ability to structure data clearly are required.


2. History and Evolution

Relational databases are based on the Relational Model proposed by E. F. Codd in 1970 while working at IBM. His research paper “A Relational Model of Data for Large Shared Data Banks” laid the theoretical foundation for what we now know as relational databases.

The first commercial relational database was Oracle, released in 1979. Since then, many popular RDBMS (Relational Database Management Systems) have emerged, such as:

  • MySQL
  • PostgreSQL
  • Microsoft SQL Server
  • SQLite
  • Oracle Database

3. Core Concepts of Relational Databases

Tables

A table (also called a relation) is a collection of related data entries and consists of columns and rows.

CREATE TABLE Customers (
CustomerID INT PRIMARY KEY,
Name VARCHAR(100),
Email VARCHAR(100),
City VARCHAR(50)
);

Rows and Columns

  • Columns define the attributes or fields (e.g., Name, Email).
  • Rows represent individual records (e.g., a customer named Alice).

Primary Keys

A Primary Key uniquely identifies each record in a table. It must be unique and non-null.

CustomerID INT PRIMARY KEY

Foreign Keys

A Foreign Key is a field (or collection of fields) in one table that refers to the Primary Key in another table.

CREATE TABLE Orders (
OrderID INT PRIMARY KEY,
CustomerID INT,
OrderDate DATE,
FOREIGN KEY (CustomerID) REFERENCES Customers(CustomerID)
);

4. Relationships Between Tables

There are three main types of relationships in relational databases:

  • One-to-One: One record in a table is linked to one record in another table.
  • One-to-Many: One record in a table can be linked to many records in another table.
  • Many-to-Many: Many records in a table can be linked to many in another, often handled through junction tables.

Example: A customer can place multiple orders — this is a one-to-many relationship.


5. Advantages of Relational Databases

  • Data Integrity: Relationships and constraints prevent invalid data.
  • Flexibility: Tables can be added or modified with minimal disruption.
  • SQL Standardization: Use of SQL makes RDBMS systems broadly compatible.
  • Transactional Support: ACID compliance ensures reliable and consistent data operations.
  • Security: Role-based access controls and encryption mechanisms.

6. Limitations of Relational Databases

  • Scaling Issues: Not as horizontally scalable as NoSQL databases.
  • Complexity: Joins and normalization can increase design complexity.
  • Fixed Schema: Changing schema requires migration or downtime.
  • Performance: For large-scale unstructured data (e.g., video, IoT), relational databases may underperform.

7. Example Schema: E-Commerce System

Let’s look at a simple example with three related tables:

-- Customers table
CREATE TABLE Customers (
CustomerID INT PRIMARY KEY,
Name VARCHAR(100),
Email VARCHAR(100)
);

-- Products table
CREATE TABLE Products (
ProductID INT PRIMARY KEY,
ProductName VARCHAR(100),
Price DECIMAL(10,2)
);

-- Orders table with foreign keys
CREATE TABLE Orders (
OrderID INT PRIMARY KEY,
CustomerID INT,
ProductID INT,
OrderDate DATE,
FOREIGN KEY (CustomerID) REFERENCES Customers(CustomerID),
FOREIGN KEY (ProductID) REFERENCES Products(ProductID)
);

This design enables us to answer questions like:

  • What did a customer order?
  • When did they order it?
  • What was the price of the product?

8. Summary

Relational databases are powerful tools that structure data efficiently and reliably through the use of tables, keys, and relationships. Understanding the relational model is crucial before diving into writing SQL queries, creating normalized schemas, or designing enterprise-level applications.

In the next module, we’ll explore SQL Basics: Syntax and Structure, where you’ll write your first SQL queries and understand how to interact with relational databases using SQL.