In a recent interview for AllThingsD, Mike Rhodin, the senior vice president of IBM’s Software Solutions Group gave a very realistic description of what the future of data looks like:
[…] it comes out of the digitization of the physical world, the instrumentation of physical processes that’s going to generate huge amounts of new data, which is going to drive issues around storage, and what to do with all the data, how to analyze it. That pushes you toward real-time analytics and streaming technologies, because with real time, you don’t have to save the data — you want to look for anomalies as they occur.
This is indeed the grand picture of Big Data.
Now think for a second how many companies have such systems in place. Not many. Think now how many companies can offer as-complete-as-possible integrated systems to address these challenges. Very few.
These two answers are revealing an interesting perspective about the future of the Big Data market.
On one side we have vendors building top notch solutions—consider the new features in the relational databases, NoSQL databases, Hadoop, etc. By looking at this space you’ll have to agree that all these are excellent solutions for tackling a sub-space of the overall problem. They are getting closer and closer to offering local optimum solutions.
On other side there are the system integrators and platform vendors. Their systems may not be the best in solving every aspect of a problem, but their focus is in addressing and solving the complete problem. Their sales pitch is integration and/or specialization.
As someone writing about polyglot persistence and the 1001 NoSQL, NewSQL, and the development of the relational databases, I could be tempted to think that every company would have the budget, the know-how, and the time to take top-notch sub-systems and create solutions crafted to their problem. But looking back in time and also applying the lessons from other markets, I think it is safe to say that integrated solutions are preferred.
The lesson to be learned by both NoSQL and relational database vendors, actually by all (sub)system vendors that are playing in the Big Data market is to design products with openness and integration in mind. Very few, if any, sub-systems will be part of the grand solution if they are architected as silos. They can continue to provide the ultimate local optimum solutions, but as long as they are not architected to be part of a collaborative integrated platform they’ll lose important segments of the market. Many products I’m writing about are already following this principle, many are making steps towards being friendlier in terms of integration, and many are still taking the silver bullet approach.
Original title and link: The Grand Picture of Big Data and the Impact on the Architecture of Systems ( ©myNoSQL)