A few months ago, I got a call for a Mongodb project that involved Personalization.  First thing I asked was “what is Personalization?  I accepted the project and found out a whole new area of technology that is quickly becoming interwoven into our daily lives.  The best way to explain Personalization is by Use Case.  For example, Amazon recommends items that we might be interested in purchasing based on our demographic, behavioral, browsing and purchasing habits, Facebook sends ads our way based on our past likes and posts.  Netflix recommends movies based on our past viewing habits. All of this was difficult if not impossible with older rigid relational database technologies.  With the rise of open source unstructured database technology, Personalization has come into the mainstream.

So your CIO may be asking “Why can’t I do this with my existing Relational databases?”   Existing relational databases support transactions which means overhead in ensuring that each transaction is correct.  You wouldn’t want your bank to double deduct a ATM transaction or check incorrectly.  In addition, rigid table structures make it difficult if not impossible to manage diverse data sources and complex data models easily and fast.  In addition, once data grows exponentially, it is impossible to scale horizontally to gain adequate performance making the data usable.  Non structured Open Source databases such as Mongodb can handle complex non structured and various structured data from different data sources easily and can scale horizontally to meet Service level agreements for query response times.

Sitecore (www.Sitecore.com) web site content management software is the latest vendor requiring the use of Mongodb for it’s Personalization functionality and high availability and scalability for global high traffic commercial websites.  Expect many other vendors to make similar announcements and for Personalization to grow as Artificial Intelligence and Machine Learning technology expands into  the real world.