15 “True” Streaming Analytics Platforms For Real-Time Everything

by  Mike Gualtieri,  Forrester

Most enterprises aren’t fully exploiting real-time streaming data that flows from IoT devices and mobile, web, and enterprise apps. Streaming analytics is essential for real-time insights and bringing real-time context to apps. Don’t dismiss streaming analytics as a form of “traditional analytics” use for postmortem analysis. Far from it —  streaming analytics analyzes data right now, when it can be analyzed and put to good use to make applications of all kinds (including IoT) contextual and smarter. Forrester defines streaming analytics as:

“Software that can filter, aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any data format to identify simple and complex patterns to provide applications with context to detect opportune situations, automate immediate actions, and dynamically adapt.”

To help enterprises understand what commercial and open source options are available, Rowan Curran and I evaluated 15 streaming analytics vendors using Forrester’s Wave methodology. Forrester clients can read the full report to understand the market category and see the detailed criteria, scores, and ranking of the vendors. Here is a summary of the 15 vendors solutions we evaluated listed in alphabetical order: Read the summary in Mike’s blog.

DCL: This is a good summary of the current offerings in streaming analytics. CEP is an explicit feature of 30% of the product descriptions and is pretty much implicit in all of them. However the reader may find themselves asking several questions such as  “what is the difference between a CEP engine and a Rules engine?”  Or “what is a ‘true streaming engine’ and how fast does it have to be?” I doubt that the full Forrester report (for which you may well have to pay) will try to answer these kinds of questions. You need a book to do that!  I have to say that CEP which always involves “just-in-time” event processing with complex event pattern detection, and real-time construction of event abstraction hierarchies, could well be called “Event Streaming Analytics”.

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