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The pace of change in the field of database technology seems to be constantly accelerating. No doubt in five year’s time ^[1], Big Data and the Hadoop suite ^[2] will seem to be as old-fashioned as earlier technologies can appear to some people nowadays. Today there is a great variety of database technologies that are in use in different organisations for different purposes. There are also a lot of vendors, some of whom have more than one type of database product. I think that it is worthwhile considering both the genesis of databases and some of the major developments that have occurred between then and now.

The infographic appearing at the start of this article seeks to provide just such a perspective. It presents an abridged and simplified perspective on the history of databases from the 1960s to the late 2010s. It is hard to make out the text in the above diagram, so I would recommend that readers click on the link provided in order to view a much larger version with bigger and more legible text.

The infographic references a number of terms. Below I provide links to definitions of several of these, which are taken from The Data and Analytics Dictionary. The list progresses from the top of the diagram downwards, but starts with a definition of “database” itself:

• Database
• Hierarchical Database
• Relational Database
• Data Warehouse
• OLAP
• Data Warehouse Appliance
• Column-oriented Database
• Distributed Data
• NoSQL
• Graph Database
• In-memory Database

To my mind, it is interesting to see just how long we have been grappling with the best way to set up databases. Also of note is that some of the Big Data technologies are actually relatively venerable, dating to the mid-to-late 2000s (some elements are even older, consisting of techniques for handling flat files on UNIX or Mainframe computers back in the day).

I hope that both the infographic and the definitions provided above contribute to the understanding of the history of databases and also that they help to elucidate the different types of database that are available to organisations today.
 

 
Acknowledgements

The following people’s input is acknowledged on the document itself, but my thanks are also repeated here:

• Neil Raden (@NeilRaden) of Hired Brains Research both reviewed the infographic and make significant contributions to its contents.

Of course any errors and omissions remain the responsibility of the author.

 
Notes

From: peterjamesthomas.com, home of The Data and Analytics Dictionary and The Anatomy of a Data Function

Follow @peterjthomas