Glassbeam adds machine data analytics platform with Apache Kafka to develop applications on complex log data

Glassbeam Inc. vendor of machine data analytics, recently announced it is enhancing its industrial IoT analytics platform to include open-source stream processing model with Apache Kafka. This gives freedom for organizations to develop and deploy custom machine data analytics applications without the need to lock in their data with Glassbeam.

This transition into an industry-wide, neutral platform will drive innovation in building machine-data based solutions and services that solve an organization’s biggest data analytics challenges and remove debate on having the need to build and own a platform or invest in an off-the-shelf solution.

Glassbeam’s Semiotic Parsing Language (SPL) already provided IIoT data transformation and preparation framework for complex machine data. By integrating with Apache Kafka, Glassbeam now allows customers to not only deploy Glassbeam on-premise, but also connect to any data store by using open source Apache Kafka consumers or building their own custom consumers.

The new offering provides access to open standards with familiar environment with Kafka-based messaging bus for developers to configure flexible topics and quickly build apps on a variety of use cases involving real-time data streams. Its developer productivity eliminates the need for organizations to own, deploy, and maintain a data ingestion platform. This allows developers to solely focus on building applications.

The platform also eliminate unnecessary data preparation burden. Glassbeam platform includes a data preparation and transformation tool Glassbeam Studio, currently in beta. This reduces the developers’ time to prepare and transform complex data from hundreds of data sources. Organizations can expect as much as 100 times improvement in the time taken to prepare data. It also helps organizations focus on their core-competency – avoid the unnecessary burden to build complex, distributed systems and attempting to scale them.

Glassbeam’s core platform (SCALAR) is designed to take care of multiple clusters, data velocity and variability, and handle computing terabytes of streaming, real-time data. It also re-uses existing infrastructure investment such that it uses the consumer framework of the Kafka message bus and the host of open source consumers to connect to any existing data stores.

“Developers anywhere can now collect and enrich machine data from any source in their organization. With open access to our core platform, developers can use their existing enterprise apps, connectors and tools to deploy Kafka-based parsed data quickly,” says Puneet Pandit, co-founder and CEO, Glassbeam. “With our open platform, organizations now have the complete freedom to build custom connected-machine applications with Glassbeam without the need to build their own data ingestion platform that may not fulfil their business objectives.”

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