Beyond all the buzzwords, the Internet of Things (IoT) is shaping up to be very big business. Imagine 26 billion devices—not counting computers and smartphones—creating data, communicating with the Internet, and resulting in $1.9 trillion in global economic value-add. Those numbers, reported by Gartner, echo a report from IDC which calculated $737 billion in spending on IoT equipment and services in 2016. Add to that an often-cited EMC prediction that by 2020, the digital universe will contain 44 trillion gigabytes of data, and the data management challenges of the future become readily apparent.
The financial services industry is already embracing the Internet of Things (IOT), using devices to collect data that needs to be analyzed in real time and stored for historical analysis. The platform for all this data collection, storage, and analysis must have several winning characteristics, including:
- Highly efficient sensors and devices
- Ubiquitous high-bandwidth network connectivity
- High availability
- Fast and scalable back-end storage, computational, and analytical systems
- Streaming data collection in near real time
- The best possible security
- The ability to adjust to variable workloads
This white paper discusses how an in-memory computing platform solution like GridGain gives financial services companies the speed, scalability, and flexibility they need to build successful IoT-based applications and services.