RapidMiner Streams Integrates With Apache Storm To Tackle Advanced Analytics On Streaming Big Data

RapidMiner today announces the release of RapidMiner Streams, an application that leverages the power of Apache Storm to enable analytics on real-time streaming data. By integrating RapidMiner’s predictive analytics technology with Apache Storm, RapidMiner Streams enables real-time updates to RapidMiner’s advanced analytics in collaboration with incoming, streaming data that dictate iterative modifications to existing algorithms. The release of RapidMiner Streams means that the RapidMiner platform can now perform advanced analytics on streaming data with low latency, high throughput and enhanced computational performance. The integration of Apache Storm with RapidMiner adds to the over 1500 RapidMiner operators and subsequently enhances the platform’s ability to perform real-time predictive analytics. Use cases for RapidMiner’s analytics include analysis of free text customer feedback delivered online, data mining of millions of image files and analytics on wearable devices that prescribe users with an optimal exercise regimen to achieve their fitness goals based on historical data. RapidMiner’s analytics are enabled by way of a graphical user interface that allows analysts to combine operators for the ingestion, analysis and visualization of one or more datasets. Today’s announcement of the release of RapidMiner Streams and its concomitant integration with Apache Storm vaults the RapidMiner platform to tackle data from the internet of things and embrace use cases featuring massive volumes of streaming real-time data. As the universe of use cases that RapidMiner can handle proliferates, users should expect corresponding enhancements of the platform as customers enrich the product with feedback specific to data about their product and vertical.

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