The history of databases



Databases are a foundational element of the modern world. We interact with them even without knowing it — any time we buy something online, or log in to a service, or access our bank accounts, and so on.

The concept of a database existed long before computers. In these times, data was stored in journals, in libraries, and in hundreds of filing cabinets. Everything was recorded via paper — and that meant it took up space, was hard to find, and difficult to back up.

And then computers became available, and with them, the opportunity for better data management.


The 1960s – beginnings

The history of databases begins with the two earliest computerised examples. Charles Bachman designed the first computerised database in the early 1960s. This first database was known as the Integrated Data Store, or IDS. This was shortly followed by the Information Management System, a database created by IBM.

Both databases were forerunners of the ‘navigational database’.

Navigational databases required users to navigate through the entire database to find the information they wanted. There were two main models of this: the hierarchical model, and the network model.

The hierarchical model was developed by IBM. In it, data is organised like a family tree. Each data entry has a parent record, starting with a root record.

The network model, meanwhile, was released at the Conference on Data Systems Languages (CODASYL). It differed from the hierarchical model in that it allowed a record to have more than one parent and child record.


The 1970s – relational databases

Perhaps one of the most influential events in the history of databases came in the 1970s. It was in this decade that E. F. Codd would release his paper “A Relational Model of Data for Large Shared Data Banks”. This paper coined the term ‘relational database’ at the start of the decade, and sparked development of this new way to store and access data.

A relational database is one that shows the relationship between different data records. Unlike their navigational counterparts, relational databases would be searchable. They would also be more space-efficient, meaning reduced data storage costs.

What followed was the creation of INGRES by Michael Stonebreaker and Eugene Wong at the University of California, Berkeley. INGRES, short for Interactive Graphics and Retrieval System, was a relational database model, proving the viability of Codd’s ideas. INGRES used a query language called QUEL.

IBM then released their take on a relational database. Known as System R, it was the first in the history of databases to use structured query language (SQL).


The 1980s – growth and standardisation

The 1980s in the history of databases marked a time of growth. Particularly, it was the time of growth for the relational database model. Earlier navigational models faded, while the commercialisation of relational systems saw this type of database rise in use and popularity.

The 1980s also saw SQL become the standard language used for databases, which we still use today.

Another noteworthy event for the history of databases was the emergence of Object-oriented database management systems (OODBMS). This concept appeared in the mid-80s. Object databases would view data as ‘objects’. They would work with programming languages that supported the ‘object-oriented’ approach.


The 1990s – the internet

The early days of object-oriented database management did not see the idea as a popular one. This was partially due to the costs and time it would take to rewrite existing databases to support the approach. However, object oriented database systems grow more popular in the 90s.

Another key event impacting the history of databases in the 90s was the creation of the World Wide Web. High investments in online businesses fuelled demand for client-server database systems. As such, the internet helped to power exponential growth of the database industry in the 1990s.

A notable outcome of this was the creation of MySQL in 1995, which was open source. This meant that it provided an alternative to the database systems offered by big companies like Oracle and Microsoft. MySQL is still used by many today.


The 2000s – NoSQL

In 1998, the term NoSQL (not only structured query language) was coined. It refers to databases that use query language other than SQL to store and retrieve data. NoSQL databases are useful for unstructured data, and they saw a growth in the 2000s.

This is a notable development in the history of databases because NoSQL allowed for faster processing of larger, more varied datasets. NoSQL databases are more flexible than the traditional relational databases that had risen the decade before.


The 2010s – distributed databases and cybersecurity

The 2010s were a decade of increased data awareness, with the rise of big data and an increased emphasis on data protection. And these trends naturally inform the history of databases.  

Having earned its name the decade before, big data was a major buzzword of the 2010 — and big data meant big databases to house it. With the need to collect, organise and make use of such huge reams of data, automation software has grown a popular tool when interacting with databases.

This is the decade where the value of data truly hit the public consciousness. And, with it, the importance of keeping data safe. Legislation like GDPR and the NIS directive only served to further highlight the importance of keeping data — and so databases — well protected and secure.

Alongside this is the impact of globalisation on the evolution of databases, with more attention going to distributed databases. These are databases that store data across multiple physical locations, rather than in one place.


The history of databases

The history of databases is a rich one, stretching as far back as the advent of the computer as we know it today. Databases have grown alongside computers, and changed immensely since their inception in the 1960s.

Now, we can only wait to see what the future holds for the evolution of databases.


Useful links

What is a database? A 500-word overview

ELI5: the relational vs non-relational database

What is intelligent process automation?


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