Alan Kay, the Xerox PARC founder and visionary computer scientist, once said, “don’t worry about what anybody else is going to do… The best way to predict the future is to invent it. Really smart people with reasonable funding can do just about anything that doesn’t violate too many of Newton’s Laws!”
Alan wasn’t the first* to express the view that the future can, at least in part, be invented, but he was one of its leading proponents laying much of the groundwork in the early 1970s for what would become the personal computer and ultimately, the digital revolution.
For corporate leaders and their companies in the midst of the transition to becoming digital enterprises, that future is real-time computing, or what I prefer to call ‘in the moment’ computing – the ability to make instant decisions based on live rather than stale data.
Technologists have been talking about real-time computing for years(, but it is only in the last few years that new technology platforms like SAP’s HANA (which is built around a reimagined database with built-in analytics and other functionality) and in-memory computing have made real, real-time computing possible.
So why is this important for business users? Because in our hyper-connected digital world, speed and flexibility really do matter. Customers, and consumers in particular, have become accustomed to having access to the latest information where ever they are, whenever they want it and on whatever device they choose to use. They have short attention spans, demand the best customer experience and they expect near instant gratification.
“Every second counts when you want to deliver real-time recommendations to customers based on their location, activity, or status,” said Forrester Research in a report published last month on (The Forrester Wave: In-Memory Database Platforms, Q3 2015).
Forrester points out that the traditional approach of storing data on disk and later integrating and analyzing it isn’t good enough anymore; decision makers need the perfect recommendation in seconds, not days or weeks. “Storing and processing customer data, events, and clickstreams in memory supports such sub-second, low-latency access,” said Forrester. Translation? To be relevant in today’s digital economy, it has to be able to analyze and deliver insights on huge volumes of disparate data – quickly.
It has got to be fast and able to deal with huge volumes of disparate data to be relevant in today’s digital economy.
In-memory DB uses
Here are some examples. The reservations systems for hotels, concerts, sports events, restaurants, and car rental companies. They all use in-memory data platforms to deliver the enhanced customer experiences that allow you or me to choose a table, seat, or room in real time, even when hundreds and thousands of others are doing the same thing at that the exact same moment.
Or consider directors in today’s corporate boardrooms. They need to be able to make decisions immediately based on up-to-the minute information, and to assess investment opportunities in real time rather than having to wait hours, days or perhaps weeks for IT to run a report.
Sounds simple? Yes, but until recently storing and processing larger amounts of data in memory was not an option because the hardware was prohibitively expensive and the old-style (legacy) relational database products were too slow and cumbersome and incapable of handling the huge volumes of structured and unstructured data that modern applications, including predictive analytics, now depend on.
Over the past few years this has changed. Today’s disruptive in-memory database platforms like SAP’s , are changing the way we build and deliver systems of customer engagement (replacing old and limited customer relationship management (CRM) systems) and are transforming the practice of analytics, predictive modeling, and business transaction management.
Digital enterprise OS
To be successful in the digital economy, companies need to be running real-time applications on a true and complete in-memory data platform – think of this ‘platform’ as the ‘operating system’ for a digital enterprise.
Although some companies have been using real-time apps for decades, they previously required extensive application coding and customization to deliver extreme performance and that limited their use to a few specialized functions like stock trading and fraud detection. But this is no longer the case.
Today, for example, major retail stores, mid-sized retailers, and eCommerce sites like Ebay and Amazon have started to exploit in-memory data platforms and big data (structured, like sales records and unstructured, like customer comments on social media) in a big way. Similarly equipment manufacturers are using sensors, machine generated data and in-memory systems to analyze the performance of everything from tractors and jet engines to production line machinery and predict in real-time when a part might fail and need replacing.
“The in-memory database market is new but growing rapidly as enterprise architects look at supporting new and emerging fast data insights, applications, and processes,” said the Forrester report. But not all in-memory databases are created equal. Most, for example, rely on old techniques such as data caching and unlike SAP , require additional layers of technology in order to support real world applications.
“SAP’s razor-sharp focus on in-memory technology is paying off,” said Forrester while noting that HANA already had more than 7,200 customers at the end of the second quarter this year.
Those customers are taking charge of their own futures, investing in a technology platform that provides them with a rock-solid foundation to run and extend their digital core as they transform into digital enterprises. Rather than waiting for the future, they are inventing it. The (real-time computing) train is leaving the station and it’s time for companies to jump aboard or risk being left behind.
*Footnote: The first to express this concept was scientist Dennis Gabor who was later awarded a Nobel Prize in Physics for his work on holography. In his book, “Inventing the Future,” published in 1963, he wrote “The future cannot be predicted, but futures can be invented.”