A History of Databases

From Clay Tablets to AI Agents

Databases are databases. As you read along, keep in mind that databases are indeed databases. That should simplify your understanding on concepts around databases. It is essential to understand the history of anything if you are going to use it often. We all consume databases, though differently. There is a very high chance that you shall hear this term when dealing in any computer Science niche. It could be you are interacting with professionals like software engineers, data specialists, computer scientists or information technologists or you are one.

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Introduction

There are many forms of databases that we handle on a daily basis. For instance, if you are a lab technician or a researcher, you are more likely to work with small size papers to write your 'rough work'. That is a database. We humans across the world have government systems, and for these systems to function, money is needed — thus we have taxation. The earliest databases held tax records.

Ancient Databases: Egypt and the Nile

Egyptians had databases where they would record crop quantity after harvests, land sizes, and other important information. Across the river Nile, there were seasons when the river would stretch its width — when it would flood. For this reason, it was necessary to store records of land measurements so that after the floods were gone, land would be divided as it were. These records were kept in clay tablets.

The Punch Card Revolution

For all we know, the Americans and the Europeans have really spearheaded data evolution to what we have today. During the 1880 census in United States of America, an idea was hatched. This was because the census back then never achieved its purpose — counting took so long (populations were growing) that by the time the country would finish counting, the population had grown significantly, making this whole process appear useless. An innovator by the name Herman Hollerith came up with a punched cards tabulating machine. This invention later grew to become IBM.

The Computer Age Begins

Then came the 20th century, where computers became commonly used in war to decrypt data. After the end of World War II, punch cards were replaced by computers which used magnetic tapes. As computers advanced, hard disk drives were created, which meant other database ideas came into place.

The Hierarchical and Network Models

Herman's IBM came up with the hierarchical model, while Charles Bachman came up with Bachman's network model. This did not last long before a major innovation broke into the scene.

The Relational Revolution

Edgar Codd published a paper, A Relational Model of Data for Large Shared Data Banks. This relational model has been used all along to this date. It is under the relational model that we have had the introduction and implementation of Structured Query Language (SQL). SQL is today used in MySQL, SQLite, PostgreSQL and Oracle databases, among others.

The Rise of NoSQL

It is important to mention that though SQL is widely used, other innovators have come up with non-relational databases formally referred to as NoSQL. For instance, MongoDB is a non-relational database.

The AI Era

We are now in a transition because of the emergence of Artificial Intelligence (AI). The emergence of AI has meant that AI agents like Anthropic and OpenAI are now interacting with databases more than human beings are.

Timeline at a Glance

• Ancient Egypt — Clay tablets record crop yields, land sizes, and taxes after Nile floods.
• 1880s — U.S. Census tabulation takes too long; process appears useless.
• 1890 — Herman Hollerith's punched-card tabulator solves the census problem.
• 1924 — Hollerith's company becomes IBM.
• 1940s — Computers used in World War II for code-breaking.
• Post-WWII — Punch cards replaced by magnetic tape computers.
• 1960s — Hard disk drives enable true database systems.
• 1960s — IBM's hierarchical model and Charles Bachman's network model.
• 1970 — Edgar Codd publishes the relational model.
• 1970s — SQL is introduced and implemented.
• 1980s–1990s — Relational databases dominate enterprise computing.
• 2000s — NoSQL databases like MongoDB emerge.
• 2020s — AI agents (Anthropic, OpenAI) interact with databases more than humans.