SQL And Databases Introduction: Why SQL Still Reigns in 2025

I’ll be honest, SQL wasn’t the first tech skill I learned. But it’s the one I’ve used everywhere since.

From analyzing marketing data to querying a Django app’s backend, SQL has followed me through every role and project. And I’m not alone.

Over 85% of companies rely on relational databases and SQL to power their internal systems, dashboards, and data pipelines.

So if you’re asking, “Should I learn SQL in 2025?” the answer is a hard YES.

In this guide, I’ll walk you through everything from what SQL is, how databases work, what tools you’ll actually use, and how to master real-world querying. Whether you’re here for backend dev, data science, or just curiosity you’ll leave ready to speak fluent SQL.

What Is a Database? And Why Should You Care?

At its core, a database is just a structured way to store information.

Imagine a massive Excel workbook where each sheet is a table, every row is a record, and each column is a field. Now give that workbook superpowers, indexing, multi-user access, integrity constraints, and querying abilities. That’s a database.

A relational database stores data in tables with relationships between them (hence “relational”). The language used to work with these is SQL – Structured Query Language.

Why Databases Matter

You use databases every day, whether you realize it or not:

• Signing into a website → your info is retrieved from a database
• Searching for products on Amazon → results are fetched using SQL
• Streaming Netflix → user preferences are stored and matched with content via SQL

Top SQL Databases in 2025: Which One Should You Learn?

Not all databases are created equal. Let’s explore the most popular ones and what they’re best suited for.

1. MySQL

• Owned by: Oracle
• Best for: Web apps, WordPress, LAMP stack
• Pros: Easy to use, widely supported, free
• Cons: Lacks some PostgreSQL features like full JSONB indexing

2. PostgreSQL

• Open-source & community-driven
• Best for: Data-heavy apps, analytics, modern applications
• Pros: Advanced features, performance tuning, extensions
• Cons: Slightly steeper learning curve

3. SQLite

• Best for: Mobile apps, small local storage
• Pros: Zero config, embedded in Android/iOS
• Cons: Not meant for multi-user web apps

4. SQL Server (Microsoft)

• Best for: Enterprise, Windows-based orgs
• Pros: Deep MS ecosystem integration
• Cons: License cost, Windows focus

5. Oracle DB

• Best for: Banking, massive enterprise systems
• Pros: High security, robust
• Cons: Expensive, complex licensing

SQL vs NoSQL: What’s the Difference?

You might’ve heard about NoSQL databases like MongoDB or Firebase. So how are they different?

Rule of thumb: Choose SQL when structure and integrity are important. Choose NoSQL when scalability and flexibility matter more.

SQL Basics: The Language of Data

Let’s get our hands dirty with the actual commands.

SELECT – Fetch Data

SELECT name, email FROM users;

SELECT name, email FROM users;

INSERT – Add New Data

INSERT INTO users (name, email) VALUES ('Ali', 'ali@example.com');

INSERT INTO users (name, email) VALUES ('Ali', 'ali@example.com');

UPDATE – Modify Existing Data

UPDATE users SET email = 'newemail@example.com' WHERE id = 3;

UPDATE users SET email = 'newemail@example.com' WHERE id = 3;

DELETE – Remove Data

DELETE FROM users WHERE id = 4;

DELETE FROM users WHERE id = 4;

These four make up the DML (Data Manipulation Language) core of SQL.

Going Deeper: DDL, Joins, Aggregates & More

DDL: Structuring the Database

CREATE TABLE customers (
  id INT PRIMARY KEY,
  name VARCHAR(50),
  joined_date DATE
);

CREATE TABLE customers (
  id INT PRIMARY KEY,
  name VARCHAR(50),
  joined_date DATE
);

CREATE, DROP, ALTER are all part of the DDL (Data Definition Language).

JOINs – Connect Data Across Tables

SELECT c.name, o.amount
FROM customers c
JOIN orders o ON c.id = o.customer_id;

SELECT c.name, o.amount
FROM customers c
JOIN orders o ON c.id = o.customer_id;

JOINs are powerful. They let you stitch together data across multiple tables.

Types of JOINs:

• INNER JOIN – only matching records
• LEFT JOIN – all from left + matches
• RIGHT JOIN – all from right + matches
• FULL JOIN – everything

Aggregations – Summarize Data

SELECT product, SUM(sales) FROM orders GROUP BY product;

SELECT product, SUM(sales) FROM orders GROUP BY product;

Common functions: COUNT(), SUM(), AVG(), MAX(), MIN()

Indexes, Primary Keys, and Performance

Ever searched a PDF using Ctrl+F vs scrolling manually? That’s what an index does.

• Primary Key: Uniquely identifies each row
• Index: Speeds up lookups
• Foreign Key: Ensures referential integrity

Avoid indexing everything, it increases write time and storage. Index what you query often.

Transactions & ACID Principles

Transactions are bundles of operations that succeed or fail together.

BEGIN;
UPDATE accounts SET balance = balance - 500 WHERE id = 1;
UPDATE accounts SET balance = balance + 500 WHERE id = 2;
COMMIT;

BEGIN;
UPDATE accounts SET balance = balance - 500 WHERE id = 1;
UPDATE accounts SET balance = balance + 500 WHERE id = 2;
COMMIT;

SQL supports ACID:

• Atomicity: All or nothing
• Consistency: Valid state
• Isolation: No side effects
• Durability: Data is permanent

Real-World Use Case: Analyzing Sales Data

You work at an e-commerce company. You want to:

1. List top 5 products by revenue
2. Show average order value per region
3. Flag any user who spent over ₹50,000

SELECT product, SUM(total) AS revenue
FROM orders
GROUP BY product
ORDER BY revenue DESC
LIMIT 5;

SELECT product, SUM(total) AS revenue
FROM orders
GROUP BY product
ORDER BY revenue DESC
LIMIT 5;

Common Pitfalls for Beginners

How to Practice SQL Like a Pro

Free Tools

• SQLBolt
• Mode SQL Tutorial
• LeetCode SQL Challenges

Setup SQLite Locally

brew install sqlite3
sqlite3 test.db

brew install sqlite3
sqlite3 test.db

Beginner-Friendly Learning Paths

FAQs

Recap: What You Now Know

• What SQL is and how databases work
• The top relational databases in 2025
• How to read and write basic SQL queries
• How JOINs, GROUP BY, and indexes work
• Real-world usage and best practices
• How to continue your SQL learning path

If you’ve read this far, you’re already ahead of 90% of people who “want to learn SQL.” Now go open up SQLite or SQLBolt, and make your first query.

Read More on This Topic

• Data Cleaning in Python – Handle Missing, Messy, Wrong Data
• Exploratory Data Analysis (EDA) in Python – Full Guide
• Learn SQL for Beginners: A Practical Introduction to Databases
• SQL & Databases 101: Fundamentals of Relational and NoSQL Databases

Additional Resource:

SQLBolt – Learn SQL Interactively