Apache Ignite: real-time processing of IoT-generated streaming data (May 10 webinar)

Apache Ignite: real-time processing of IoT-generated streaming data (May 10 webinar)Your watch; your car; the lights in your home; your home security system; your television – perhaps even your refrigerator. All of these “smart devices” have electronics, software, sensors and embedded devices that connect to the internet via Wi-Fi and are collectively part of what’s known as “The Internet of Things” (IoT).

These devices gather local data -- what’s happening around them -- to the benefit of the consumer. But if your organization is focused on any of these devices then the only way to ensure that you’re continually optimizing your business is to collect and analyze this data.   

Your IoT solution should be able to transfer huge 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 in order to rapidly make the best business decision. 

During our May 10 webinar, “Apache Ignite: real-time processing of IoT-generated streaming data,” GridGain product manager Denis Magda will show you 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 open-source 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.

Sign-up now to reserve your spot! May 10 at 11 p.m. Pacific and 1 p.m. Eastern.