Santa Clara-based machine data analytics vendor Glassbeam recently revealed details of a new version of Glassbeam SCALAR marked by deep integration with Apache Spark. Apache Spark is a parallel data processing framework that facilitates real-time analytics, machine learning and real-time analytics by storing the results of data operators in memory and performing low latency, iterative calculations on in memory computational results. Known for its ability to automate the parallelization of tasks and jobs, Spark boasts operational efficiencies over MapReduce by a factor of 100 with respect to the execution of calculations on large datasets. Glassbeam SCALAR’s integration with Apache Spark enhances its computational capabilities as well as the platform’s machine learning functionality and capacity to perform real-time analytics on streaming datasets by means of the Spark Streaming and MLLib components of the Spark stack. Built on Cassandra, Spark’s addition to the Glassbeam’s cloud analytics platform gives it the benefits of Cassandra’s distributed data management architecture in addition to Spark’s computational, analytic and machine learning functionality. As such, today’s announcement strengthens Glassbeam’s position in the nascent but exploding internet of things analytics space by augmenting its ability to ingest, process and analyze massive amounts of data as well as enhancing Glassbeam SCALAR’s advanced analytics, machine learning and predictive analytics capabilities.
Glassbeam Inc today announces $2M in additional funding by means of a capital raise led by the VKRM group. Glassbeam also revealed details of a strategic partnership with Tableau whereby Tableau can integrate with SQL-compliant extracts from Glassbeam to enable customers to more effectively visualize machine data and discern trends by way of Tableau’s powerful visualization capabilities. In an interview with Cloud Computing Today, Glassbeam CEO Puneet Pandit noted that the company plans to deepen its strategic partnership with Tableau by delivering offerings from Tableau that are specific to Glassbeam, pending the finalization of further negotiations. Moreover, Kumar Malavalli, a well known Silicon Valley technology entrepreneur, will take over as the company’s Chief Strategy Officer.
Glassbeam’s cloud-based platform is designed to ingest, process and analyze massive amounts of machine data. The platform’s deployment model involves the creation of a customized SPL file that, when deployed in the cloud, facilitates the integration of machine data into the Glassbeam platform. Glassbeam’s differentiation with the machine data analytics space involves its focus on the internet of things and the subsequent business need to rapidly transform massive amounts of complex data into actionable business intelligence. Today’s funding raise brings the total capital raised by to $8.1M. Glassbeam’s capital raise affirms its traction in the machine data space as evinced by its signing of Dimension Data as a recent customer. Expect to hear more details from Glassbeam as it continues to sharpen its product differentiation for big data analytics related to the internet of things.
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.
Machine data analytics company Glassbeam recently announced the finalization of $3M in equity funding in yet another affirmation of the vitality of the machine data space. The funding raise was led by the VKRM group. Glassbeam specializes in transforming analytics on machine data into actionable business intelligence that customers can use for a variety of use cases including optimizing application performance, more effectively understanding their customer base or making broader strategic decisions. The funding will be used for product development, the expansion of Glassbeam’s sales operations team and creation of a data science team dedicated to developing algorithmic insights from Big machine data. Glassbeam delivers its machine data analytics solution by way of a SaaS platform that provides a suite of customizable dashboards on topics such as performance or capacity management with respect to a specific IT infrastructure. Insights are derived through its semiotic parsing language (SPL), a domain specific language used for understanding relationships between elements of machine data. Glassbeam competes with the likes of Sumo Logic, Splunk and SaaS machine data analytics vendor Loggly. Current customers include IBM, Hitachi and EMC.