Today, machine data analytics vendor Glassbeam announces the release of Glassbeam SCALAR, a cloud-based platform that specializes in machine data analytics for the internet of things. In contrast to machine data analytics vendors such as Splunk and Loggly that focus on analytics related to machine data specific to data center and cloud-based IT environments, Glassbeam concentrates on complex, multi-structured log data from medical devices, sensors and automobiles in addition to data center devices.
The SCALAR platform leverages open source Big Data technologies such as Cassandra and Solr to deliver actionable business intelligence derived from structured and unstructured data. Meanwhile, SCALAR’s parallel asynchronous engine allows the platform to scale horizontally to process massive amounts of machine data that are interpreted by way of its dynamic schema functionality and semantic technologies that enrich the platform’s ability to make connections between source data elements.
A key component of the Glassbeam SCALAR platform is Glassbeam Studio, a tool that allows developers to transform unstructured machine data into structured formats for the purpose of performing a deeper dive into incoming data. Glassbeam Studio positions developers to transform data into Glassbeam’s proprietary semiotic parsing language (SPL) for understanding machine data before it is digested by the Glassbeam SCALAR platform and transformed into visual analytics as illustrated below:
Glassbeam’s output consists of visually rich, business intelligence dashboards that enable customers to make proactive, strategic decisions by way of a dynamic, real-time dashboard that illustrates trends and key attributes of source data. Key features of the Glassbeam platform in relation to the larger landscape of machine data sources and modalities of deployment are as follows:
Given that the internet of things remains to be fully realized, the release of Glassbeam SCALAR represents a bold attempt to carve out an early niche in the space by focusing on business intelligence in relation to machine data. Nevertheless, the underlying technology platform impresses by way of the breadth of its functionality as exemplified by Glassbeam Explorer, the platform’s new search and discovery tool for understanding, analyzing and visualizing machine data. Expect Glassbeam to continue to innovate and differentiate itself from the rest of the machine data analytics space, even as it captures market share related to data center devices such as servers, routers and firewall technologies. In the meantime, the race is on with respect to who will capture the early foothold in the internet of things Big Data analytics space as the industrial internet matures and gradually renders itself more and more ubiquitous in the lives of enterprises and consumers alike. Pivotal One has already placed its bets in the Internet of Things analytics space thanks to a $105 million investment from GE, but the landscape still remains wide open.