The challenge with creating an Internet of Things (IoT) analytics application today is that it often involves assembling compatible but independent components for device connections, message relay, data stream processing and visualization. And often this assembly must be done with scripting or coding in multiple languages. So, it is like assembling or installing an engine for your car before you drive to the store. And the shop manual is in a language that you vaguely understand. Great for mechanics, not so good for drivers.

GroveStreams is a young, but clear-headed IoT analytics vendor whose technology was designed to solve this ease-of-deployment problem from the get-go. Its founder, Mike Mills, spent many years developing IoT analytics applications at IBM using big data and traditional BI technology for analyzing smart meter data. From that experience, Mike saw a need for something that was faster and easier to use. His vision for GroveStreams is to minimize deployment times by having an integrated, end-to-end, IoT-specific analytics platform that handles data ingestion, analytic calculation definition and analytics visualization and doesn’t require writing script or code.

Lab Testing. To test GroveStreams, I used it to deploy a simple Raspberry Pi-based example, which took less than an hour. (See figure 1.) The platform is really easy to use, especially so when compared to other IoT solutions that require scripting to assemble and configure the necessary components. The GroveStreams examples were easy to understand with great screen shots and concise configuration instructions. Dashboards can be rapidly assembled using their Observation Studio that includes a library of graph and table widgets along with flexible controls for filtering, drilling, etc.

Figure 1.

Other Characteristics. GroveStreams is also designed to handle the volume and breadth of streaming data that is common within IoT systems. In particular, it can aggregate hundreds or thousands of event streams and then display them in a few graphical metrics to provide top-level views of complex system operation. The platform can store up to 80 million data points per raw input stream, so longitudinal analytics have a lot of headroom. Sample granularity can accommodate five samples per second. JSON encapsulation is supported, with each RESTful PUT API call capable of up to 230MB in the message body, so good flexibility to consume a wide range of IoT device data.

Because the platform is cloud-deployed, they are continuously enhancing the product. Their most recent addition allows authorization to be centrally managed and applied for user groups and communities. Hierarchical authorization rights can be applied to mirror responsibilities in a hierarchically managed organization.

GroveStreams uses a feemium pricing model with unlimited trial times for product evaluation. For more information, see www.grovestreams.com.