Technology Hype Cycles
November 1, 2012 2 Comments
I had a great idea this week. It started because I wanted to write about Business Intelligence and the benefits of flash memory for Decision Support Systems, but realised that it’s hard to mention those subjects these days without referencing Unstructured Data. That got me thinking that the hype surrounding Big Data and the way in which trends such as Cloud and In Memory Databases work.
Let’s consider the Y2K bug as an example. Back in the 1990’s it became apparent that systems which had not been coded to account for the Y2K issue might fail, so steps were taken to investigate and fix potential issues. This was clearly a Good Thing. However, as the hype surrounding Y2K exploded, every man and his dog felt the need to join the party, no matter how tenuous their connection, until it reached the point where (as I’ve mentioned before) the school that I attended when I was young received a letter from a “Y2K conformance specialist” offering to check the football pitch for “Y2K compliance”. I thought about these situations and then sketched a graph, very much like the one above, showing the hype rising inexorably, then falling away as everyone got bored of the idea (or saw through the charlatans), then finally rising slightly to reach a plateau.
I was very pleased with myself at this point and decided to write a blog showing the world how clever I was. However, a five second Google search was enough to pop that particular bubble of hubris, because it turns out that Gartner not only thought of this years ago but even publish their own Technology Hype Cycle every year. So instead of being clever it turns out I am just ignorant. No wonder Gartner’s net worth is significantly higher than mine. (And I bet you knew about this too didn’t you? So why didn’t you tell me? It could have saved us both a lot of time…)
Another thing I have to credit Gartner for is the fantastic names used to describe the phases of the cycle:
- Technology Trigger
- Peak of Inflated Expectations
- Trough of Disillusionment
- Slope of Enlightenment
- Plateau of Productivity
I love these names. The Peak of Inflated Expectations? I’m sure I’ve climbed that peak at some point. The Trough of Disillusionment? Wallowed in it. The Slope of Enlightenment? I’m hoping to climb it one day.
There are a couple of interesting things to note from this graph. Firstly, Big Data appears to be entering the phase known as the peak of inflated expectations. That sounds about right to me. Note that this is not the same thing as suggesting Big Data is a waste of time and should be ignored. Far from it. This phase is identified as the period when “a frenzy of publicity typically generates over-enthusiasm and unrealistic expectations“. My reading of this is that some people are far too keen to throw away the benefits of relational data and transactional consistency in order to embrace a new trend which they feel their organisation should be following.
The other thing that really interests me is the position of In-Memory Database Management Systems, just beginning to accelerate downwards on the big ski-slope towards the trough of disillusionment where it will join In-Memory Analytics. This, lest we forget, is identified as the point where technologies “fail to meet expectations and quickly become unfashionable“. Gartner also indicates that they believe it will be 2-5 years before these In-Memory technologies reach the plateau of productivity, where their benefits “become widely demonstrated and accepted“. Again, it’s important to emphasise that a technology located in the trough of disillusionment is not a bad technology nor one that should be avoided; it is merely one where any potential suitor should be extremely careful to ignore the marketing hype and concentrate on the facts.
Now, I am fully aware that we all see what we want to see, so you may disagree with my perception here. But for the In-Memory technologies I see a correlation between the over-hyping of the term In-Memory Database and the redefinition of Oracle Exadata X3 as a “Database In-Memory Machine“. I also see a correlation between the gradual maturity of SAP HANA and the suggestion that In-Memory technologies will achieve the plateau of productivity within 2-5 years. I am not convinced that In-Memory technologies will become “unfashionable” but I do believe that there is a danger users (and potential users) will become sceptical about the claimed benefits of IMDBs. As more vendors attempt to portray their products as In-Memory I feel this is inevitable.
Maybe you agree, or maybe you see it differently; in either case I’d love to here your views. In the meantime it’s back to the drawing board for me, to see if my latest idea will make me a million. I’ve decided to place vendors on a sort of square graph and divide it into quarters, which I am going to call the Magic Quadrangle. I just need to check if it’s been done before…
[Legal Notice: I am (unfortunately) not the inventor of either the Gartner Technology Hype Cycle or the Gartner Magic Quadrant. All copyrights and intellectual property around the Technology Hype Curve and the Magic Quadrant are therefore owned by Gartner, Inc. If you find the content discussed here interesting then I urge you to go to www.gartner.com and purchase a subscription so that you can avoid being as spectacularly uninformed as I was prior to researching this article.]