The History of SQL: From Relational Theory to Modern Data

SQL (Structured Query Language) is one of the most important technologies in the history of computing. It powers everything from ecommerce websites to enterprise dashboards to AI-ready data warehouses.

But where did SQL come from? How did it become the standard language for databases? In this article, we’ll explore the origins of SQL, how it evolved over the decades, and why it remains essential today.

The Origins: Relational Theory (1970)

SQL is based on relational database theory, which was introduced in 1970 by British computer scientist Dr. Edgar F. Codd, who worked at IBM.

In his landmark paper, “A Relational Model of Data for Large Shared Data Banks,” Codd proposed that:

• Data should be stored in tables (relations)
• Each table should consist of rows and columns
• Relationships between tables should be managed using keys, not pointers

This was revolutionary: it introduced a mathematical model that made databases easier to query, manipulate, and reason about.

IBM System R and the Birth of SQL (1974–1979)

In the mid-1970s, IBM researchers began building a prototype relational database system called System R to demonstrate Codd’s ideas.

As part of that project, they developed a new query language called SEQUEL (Structured English Query Language). It was later shortened to SQL due to trademark issues.

System R showed that:

• A relational model could work in practice
• SQL could be used to write readable, flexible queries
• Declarative syntax was more user-friendly than earlier database languages

The Rise of Commercial SQL Databases (1980s)

By the early 1980s, multiple companies began offering commercial SQL-based database systems:

• Oracle: Released the first commercial SQL RDBMS in 1979 (Oracle v2)
• IBM: Launched DB2 in 1983
• Microsoft: Released SQL Server (co-developed with Sybase) in 1989
• Ingres: One of the first open-source SQL database projects

SQL became the ANSI (1986) and ISO (1987) standard query language for relational databases, further cementing its dominance.

SQL Becomes Ubiquitous (1990s–2000s)

Throughout the 1990s and early 2000s, SQL became the backbone of data in:

• Enterprise software
• Web applications
• ERP and CRM platforms
• Business intelligence (BI) tools

New SQL dialects and database platforms emerged:

• PostgreSQL (open source, standards-compliant)
• MySQL (lightweight and widely used in web apps)
• SQLite (embedded SQL database for mobile/desktop apps)

This era also introduced SQL injection attacks, prompting greater focus on query security and input validation.

Big Data & NoSQL: A Temporary Detour (2010s)

The 2010s saw a wave of NoSQL databases—like MongoDB, Cassandra, and DynamoDB—emerge to support flexible schemas and massive scale.

Some headlines predicted “the death of SQL.” But instead of disappearing, SQL adapted:

• NewSQL systems like CockroachDB and Google Spanner emerged
• Columnar databases like BigQuery and Snowflake use SQL interfaces
• Even MongoDB added SQL-like querying via the Atlas SQL interface

SQL became the unifying interface across relational and non-relational systems.

SQL Today: Still Thriving (2020s)

SQL is more relevant than ever:

• It’s the universal language of data analytics and business intelligence
• It powers data science workflows, ML pipelines, and AI agents
• New tools like Galaxy make SQL more accessible and collaborative
• SQL is integrated into every cloud platform (AWS, GCP, Azure)

It’s also one of the top languages in developer surveys like Stack Overflow’s annual survey.

Why SQL Has Endured

Here’s why SQL has stood the test of time:

• Simplicity: Easy to read and write
• Expressiveness: Powerful enough to handle complex logic
• Declarative: Focus on what you want, not how to get it
• Portable: Works across many database systems
• Standardized: ANSI/ISO standard ensures long-term stability

Want to learn the basics? Check out How SQL Works or Write Your First SQL Query.

Final Thoughts

SQL isn’t just a database language—it’s a pillar of modern data infrastructure. What started as a research experiment in the 1970s has become the most widely used way to interact with structured data.

Whether you’re querying a production app, building a data pipeline, or exploring trends in a dashboard, SQL is here to stay.

Get started now in the Galaxy SQL Editor—your modern workspace for fast, schema-aware SQL.

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