ParStream Introduces Analytics Platform for IoT

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ParStream has introduced an analytics platform purpose-built for the speed and scale of the Internet of Things (IoT). The ParStream Analytics Platform is designed to scale to handle the massive volumes and high velocity of IoT data and is expected to help companies generate actionable insights by enabling analysis with greater flexibility and closer to the source.

In additon to integrating with Knime, statistical libraries like R, and other machine learning engines, the platform enables the seamless integration of Datawatch, a visualization tool for IoT analytics, and supports the high-velocity ingestion needs of IoT,  with close integration with Informatica’s collection tool, Vibe.  ParStream has committed to a tight integration with these two platforms to avoid potential compatibility issues between the platforms. 

“When we say ‘integrating,’ it means working with the R&D team from Informatica and Datawatch to change our code to better support it,” explained the CEO of ParStream, Peter Jensen. This means, for example, that when Datawatch or Informatica releases an update, the ParStream development team will test it beforehand to make sure it syncs up with the ParStream Analytics Platform.

The ParStream database is unique in that it is not open source and was built from scratch and written in the C programming language. “We wanted to have full control over this to create the fastest analytical database,” stated Jensen. 

It is important that companies ask themselves what type and how much data they plan on analyzing because ParStream may not be the right database for everyone, noted Jensen.

ParStream aims to provide high performance by providing a platform that is able to analyze many terabytes of data within seconds and supporting multiple users able to import that data at the same time. This is the typical workload for databases when it comes to the IoT, notes Jensen.

Two additional unique capabilities of the ParStream platform are its geo-distributed analytics and ability to rapidly conduct follow-up questions and queries with the data.

According to the company, organizations using the ParStream Analytics Platform can expect to roll out IoT applications twice as fast versus integrating components in-house from different vendors. Additionally, it is estimated that users will require 30% less resources for testing and supporting applications, because the components are proven, fully tested, integrated and ready to address the needs of IoT.

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