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The History of SQL | SQL & Databases Tutorial

Learn about The History of SQL in this comprehensive SQL & Databases development tutorial. From IBM to the World.

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🚀 LEVEL UP TO SENIOR:Unlock 500+ Advanced Practical Challenges & Exercises.

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1IBM System R

SQL was originally developed at IBM in the 1970s by Donald Chamberlin and Raymond Boyce. It was designed to manipulate and retrieve data stored in IBM's original relational database management system, System R. Today, almost every major enterprise runs on a descendant of this system.

2Step-by-Step Breakdown

What is SQL?. Structured Query Language (SQL) is the standard language for dealing with Relational Databases. If you want to store, manipulate, or retrieve data, you use SQL.

The Relational Model. In SQL, data is stored in Tables (like Excel spreadsheets). Each Table has Columns (attributes) and Rows (records). Tables are related to each other.

Declarative Language. SQL is Declarative, not Imperative. You don't tell the database HOW to find the data. You just declare WHAT data you want, and the DB figures out the fastest way to get it.

SQL Standards. SQL is an ANSI/ISO standard. However, different databases (PostgreSQL, MySQL, SQL Server) add their own custom extensions and syntax variations.

Knowledge Check. Because SQL is a 'Declarative' programming language, what does the developer focus on when writing a query?

→Specifying WHAT data is needed, letting the engine figure out how to get it
→Writing the exact loops and algorithms for HOW to search the hard drive

DDL vs DML. SQL is split into categories. Data Definition Language (DDL) creates tables (CREATE, DROP). Data Manipulation Language (DML) modifies data (INSERT, UPDATE, DELETE).

DQL (Queries). Data Query Language (DQL) is all about retrieving data. The primary command is SELECT. This is what you will spend 80% of your time writing.

ACID Properties. Relational DBs guarantee ACID: Atomicity, Consistency, Isolation, Durability. This means if a bank transfer crashes halfway, the DB automatically rolls it back. No half-transactions.

Why learn SQL?. Frameworks change every 2 years. SQL was invented in the 1970s and is still the most in-demand backend skill today. It is timeless.

Summary. SQL is the foundation of backend engineering and data science.

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Accessibility (A11y)

1Explain Technical Database Terms in Plain Language, Not Just Tooltips

Introductory SQL content that uses acronyms like DDL, DML, and ACID should expand each acronym in the visible text, since tooltips triggered only on mouse hover are often unreachable to screen reader and keyboard-only users.

SEO Implications

1
Beginner SQL Explainer Content Ranks Well for High-Volume Definitional Searches
Queries like 'what is SQL' and 'SQL vs relational database' are extremely high-volume, evergreen searches. A clear, well-structured explainer page with proper heading hierarchy can capture significant organic traffic for a developer-education site.

Best Practices

Learn the Declarative Mental Model Before Memorizing Syntax

SQL describes WHAT data you want, not HOW to fetch it — the query planner decides the retrieval strategy. Internalizing this early prevents beginners from trying to write procedural, step-by-step logic inside a SQL statement.

Learn to Categorize Every Command as DDL, DML, or DQL

Knowing that CREATE/ALTER/DROP are DDL (structure), INSERT/UPDATE/DELETE are DML (data), and SELECT is DQL (queries) helps you reason about which commands change your schema versus your data versus just reading it.

Frequent Bugs

THE BUG

A beginner tries to write step-by-step looping logic (like a for-loop) directly inside a SQL statement and it fails or behaves unexpectedly.

THE FIX

SQL is declarative, not imperative — you can't describe an algorithm's steps directly in standard SQL. Express the desired result set with SELECT, WHERE, JOIN, and GROUP BY, and let the query planner determine execution strategy.

THE BUG

Code written for one database engine (e.g. MySQL-specific syntax) fails when run against Postgres or SQL Server.

THE FIX

SQL is an ANSI/ISO standard, but each vendor adds its own extensions (e.g. LIMIT vs TOP vs FETCH FIRST). Stick to standard SQL where possible and check vendor documentation before relying on engine-specific features in portable code.

Real-World Examples

Choosing the Right SQL Category for a Migration Script

A team writing a database migration needed to both change the users table's structure and backfill a default value into existing rows.

-- DDL: changes the structure
ALTER TABLE users ADD COLUMN status TEXT DEFAULT 'active';

-- DML: changes the data
UPDATE users SET status = 'active' WHERE status IS NULL;

Interview Prep

Pascual Vila

Frontend Instructor // Code Syllabus

Common Pitfalls & Errors

The Error //

Trying to write imperative, step-by-step logic inside a plain SQL query

-- Wrong mental model: trying to 'loop' manually
-- (SQL has no for-loop in a plain query)

-- Correct: declare the result you want
SELECT name, age FROM users WHERE age >= 18 ORDER BY age;

The Solution //

SQL is declarative — you describe the desired result set, not the algorithm to fetch it. Express the goal with SELECT, WHERE, JOIN, and GROUP BY, and reserve procedural extensions like PL/pgSQL or stored procedures for cases that genuinely require step-by-step logic.

The Error //

Assuming SQL syntax is fully portable across every database engine

-- Postgres / MySQL
SELECT * FROM users LIMIT 10;

-- SQL Server
SELECT TOP 10 * FROM users;

The Solution //

SQL is an ANSI/ISO standard, but Postgres, MySQL, and SQL Server each add their own extensions and quirks (e.g. LIMIT vs TOP vs FETCH FIRST). Check the target engine's documentation before relying on non-standard syntax in code meant to run on multiple databases.