Software AG is the second largest software company in Germany… and you can guess who the largest one might be… the firm’s latest product releases are firmly focused on the Internet of Things (IoT).
Software AG has expanded the capabilities of its Apama Community Edition software with a new Internet of Things (IoT) analytics kit, provided free of charge as open source software under the Apache License, v2.0, along with the ability to run on Raspberry Pi.
What this means is that a different version of Apama Community Edition is also now available as a re-distributable runtime.
Apama Community Edition is a free version of the Apama Streaming Analytics platform. It enables developers to download the Apama software, build ‘streaming analytics applications’, and put those applications into production. Apama Community Edition contains most of the functionality and features of the premium version and enables developers to develop and run small- to medium-sized scale proof-of-concepts, projects and applications.
The IoT Analytics Kit for Apama Community Edition contains a set of event-based, analytical microservices used for the development of IoT applications.
Examples include analytics that calculate the ‘normal’ range of numeric values and create an alert if these ranges have been exceeded or breached. Other analytic services include Threshold Breach, Missing Data, Quasher, Variance, and Gradient.
A slice of Raspberry Pi
Additionally, Apama Community Edition now runs on Raspberry Pi and can be used to build, for example, streaming analytics applications or act as an ARM-based Edge gateway or Edge device. Included with the software are project samples, complete documentation as well as a plug-in that leverages the GPIO (General Purpose Input/Output) pin on the Raspberry Pi computer, which allows other devices to connect seamlessly.
The Apama Core Community Edition Runtime allows developers to build applications on top of Apama Community Edition and then distribute these applications free of charge.
Why is streaming analytics important?
As Harrine Freeman explains here on dataversity, “Stream processing analyzes and performs actions on real-time data though the use of continuous queries. Streaming analytics connects to external data sources, enabling applications to integrate certain data into the application flow, or to update an external database with processed information.”
In less technical language, this means that IoT devices can channel the data they create into software management applications in a stream and there allow us to work with live data coming in from the IoT as it is actually produced.
The older world of data crunching relies on what is logically known as ‘batch processing’ where data is processed at defined times in defined chunks. Given the live nature of many of the IoT’s sensors and devices, streaming analytics will become an increasingly important part of the way the IoT now develops.