bill vorhies Summary:  Yes these two seeming dissimilar and incompatible standards are indeed on a direct collision course and Gartner says we will see it come to pass by 2017.

Ordinarily we think of things about to collide as destructive, a bad thing.  But in this case, not so much.  rams butting headsThis will make it easier on the buyer/user and offer a larger market place for the surviving competitors. And just when should we fasten our seatbelts?  Gartner says “By 2017, all leading operational DBMSs will offer multiple data models, relational and NoSQL, in a single platform.”

Prior to this Magic Quadrant report in 2014 Gartner kept these separate and reviewed the very mature OLTP market separately from NoSQL.  But less than a year ago now Gartner, the king of naming conventions changed this category name from OLTP to ODBMS (Operational Database Management Systems).  Why?  Because NoSQL and NewSQL offerings that had previously been “overwhelmingly supplemental to traditional relational DBMS deployments, not destructive” per Nick Heudecker, Research Director – Information Management at Gartner, are now seen as viable contenders to replace or at least be combined with relational systems in the future.

What’s driving this?  No less than Big Data.  Specifically unstructured and semi-structured data that in the past was difficult to capture and process.  This includes not only the elements of Volume and Variety, but also Velocity as we capture more click stream and IoT data.  Here’s what the “Magic Quadrant for Operational Database Systems” published October 16, 2014 looks like.

Gartner ODBMS Magic Quad Oct 2014

It seems strange to see Oracle and SAP on the same chart with Cloudera and MapR but here’s Gartner’s logic.  First of all Gartner defines a DBMS “as a complete software system used to define, create, manage, update and query a database, by which we mean an organized collection of data that may be structured in multiple formats and stored in some form of storage medium.”

Second and perhaps most obvious, Gartner has found it necessary to recognize two categories of unstructured or semi-structured data that have ever growing importance to business operations:

  • Interaction data is the fabric of information in the social sphere, generated from one or more people interacting with devices and one another. Interactions are associated with social phenomena: new sources, such as tweets, Facebook posts and weblogs, that record customers’ activity and behavior. They are also associated with more traditional, but formerly little-used, types of data, such as email archives, content repositories, and voice and video recordings.”
  • Observation data is generated by connected devices, which enable and document much of the impact of mobile technology and other new use cases. Examples are geolocation data in Internet Protocol data records, data from the Internet of Things, and extensions of the call data records that were so important to early mobile phone providers’ efforts to model customer behavior. This data enables a new class of applications that provides and restores context for simple transactions.”

Gartner’s survey shows that 75% or respondents use interaction data in transactions and an additional 50% use observation data in transaction processing.

Here we are in 2015 and no truly combined relational and non-relational DBs are currently being offered on a single platform.  True you can buy them separately from Oracle, IBM, and others but not yet in integrated form.  If you are a Hadoop user, you know you typically get Key Value, Columnar, and Graph in a single distribution but not relational.  In some ways, NewSQL like NuoDB that is still SQL based and relational but with some capability to handle semi-structured data may be the closest.

But Gartner’s observation that unstructured and semi-structured data have become increasingly central to business operations is clearly true.  And as a competitive driver it seems reasonable that competitors would set out to conquest each other’s space by offering an integrated offering.  Still, there’s a lot of new technology required to bring these two worlds together and according to Gartner, only about another two years until we see this mighty collision.


July 15, 2015

Bill Vorhies, President & Chief Data Scientist – Data-Magnum – © 2015, all rights reserved.


About the author:  Bill Vorhies is President & Chief Data Scientist at Data-Magnum and has practiced as a data scientist and commercial predictive modeler since 2001.  Bill is also a Senior Contributing Editor for Data Science Central.  He can be reached at:


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