The Internet of Things (IoT) is more than a bunch of sensors. Sensors and embedded devices gather data about the surrounding environment, but what you do with this data is what truly matters. A bunch of sensors won’t optimize your business. Collecting and analyzing the data that those sensors produce will. As such, your IoT solution should be capable of transferring enormous amounts of data to storage or the cloud for additional processing and analysis. Quite often, processing of endless streams of data must be done in real-time or near real-time in order to rapidly make the best business decision.
During this 1-hour webinar, we will explain and demonstrate how to build a fast data solution that can receive endless IoT-generated streams and process them in real-time using Apache Ignite’s distributed in-memory computing platform. In particular, you will learn the following:
· How to stream data to an Apache Ignite cluster from embedded devices
· How to conduct real-time data processing on this stream using Apache Ignite
The Apache Ignite in-memory computing platform provides the ability to ingest and analyze streaming data using a high-performance and scalable distributed architecture. Traditional disk-based architectures can’t keep up with the speed and volume of IoT data. Apache Ignite uses in-memory technology to achieve performance gains of 1000x or greater over disk-based solutions. At the end of this webinar, you’ll understand why this makes Apache Ignite an excellent fast data solution for working with IoT-related data streams.
VP, Developer Relations in R&D at GridGain; Apache Ignite committer and PMC member