big dataThe advent of the Internet and World Wide Web changed many things in the technology landscape. Information began to become widely accessible. Individuals began to connect with one another online. Merchants began to market and sell their products digitally, sometimes to entirely new markets or customer demographics.

Each new connection and behavior enabled by the web had a corresponding impact on data management systems. In the world of data storage and retrieval, the usage patterns of relational database management systems (RDBMS) had been relatively stable and predictable for quite some time.

Invented in 1970 by E.F. Codd, RDMSs were marketed and used commercially in the 80s for operational data entry. As the Internet and the World Wide Web emerged in the 90s, RDBMSs began to connect with a quantity of end users that designers had never anticipated. Instead of being used only by internal data entry specialists to support manually operated point of sale systems or business oriented reporting and analytic tools, RDBMSs began to be used to build client applications that were websites or email marketing services, directly serving information to and executing transactions initiated by millions (and eventually billions) of individuals worldwide.

NoSQL Replaces RDBMS

The use of RDBMSs to power millions and billions of interactions and transactions created an entirely new domain for data management, one that had to be built from the ground up with a new and changing set of requirements in mind.

In the early 2000s, Google began to abandon relational databases for their Internet search engine and web crawler while continuing to use RDBMSs for operational data stores such as advertising systems (which allowed them to monetize). It began to develop new data management technologies (including Hadoop) that provided simpler interfaces specifically for application developers.

At the same time, the tech industry began to see a massive uptick in the amount of data generated by individuals and by enterprises. Fueled by near ubiquitous consumer access to web and mobile applications, enterprises started amassing ever larger volumes of data, including rich media, logs of user clicks and the diagnostics created by the application code.

This new class of data assets led to the creation of entity-centric systems, specializing in storing rich complex data associated with an end user, rather than individual pieces of content or data records. These systems collectively have also been called NoSQL because they do not natively support SQL or the relational constructs that underpin SQL. Read more

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