Attention business leaders: We’ve just reached another inflection point of how data can be used to drive better business results.The Internet giants have established dominance, in part, by harnessing the power of data that streams constantly across every aspect of their business.
Stream processing, on the other hand, is undergoing a relatively new technological surge and raises interesting questions. Can it provide continuous processing compared to old batch processing models? Is it fast enough to meet real-time application requirements? Can it include historical data for a richer context? How resilient is it?
This leads to conundrum #2: Technology leaders are faced with choosing two types of data processing infrastructure—stream processing technologies and database technologies. The two weren’t built together. There is no commonality at the architecture level and, once deployed, they are like two ships in the night—unaware the other exists.Stream processing is a key technology enabler for applications that enable real-time business.
It is good news that real-time applications often require small amounts of data to work. That’s because it presents a controlled way to plan for success. Even as more data flows in, technology leaders can focus on abstracting only the subset of data that’s needed.These questions will help technology leaders find the right solution for their real-time applications:
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