DataTorrent has launched a new release of its streaming data processing software that supports machine learning and offers new capabilities that make it easier to analyze trends in real time.
The new edition, DataTorrent Real-Time Streaming (RTS) 3.10, comes as the company continues to grow its channel partner community, adding systems integration giant HCL Technologies and strategic services provider Wavicle Data Solutions to its partner roster.
DataTorrent's moves come amid an increasing need for big data technology that can work in real-time with growing volumes of streaming data.
[Related: The 2017 Big Data 100]
"There's a growing need for outcome-based applications and enterprise-grade, real-time analytics capabilities," said DataTorrent CEO Guy Churchward in an interview with CRN. The capabilities in the new RTS 3.10 release, he said, are indicative of DataTorrent's move "up the stack" to provide higher-level functionality.
"We're really focused on time-to-value, getting customers into production and having them execute at scale," he said. "This is all about getting customers to become a hero as fast as possible."
The streaming data software landscape is complex with a broad range of vendors, including DataTorrent, Striim, Confluent, and Impetus Technologies, as well as major vendors IBM, SAP, SAS and Oracle, all players in the market. There are also a number of open-source streaming data technologies – many from the Apache Software Foundation – including Apex, Flink, Storm, Kinesis and Kafka.
The DataTorrent RTS platform is based on Apache Apex, the open-source unified stream and batch processing software. With DataTorrent RTS, organizations can develop, deploy and operate applications that work with streaming data in real time.
Churchward said the use of the open-source Apex technology helps customers implement DataTorrent's systems more quickly for enterprise-grade tasks.
The new DataTorrent RTS 3.10 offers expanded support for machine learning and artificial intelligence technologies, including native support for delivering analytical logic using machine scoring models written in Python or Predictive Model Markup Language.
The new edition provides an application backplane for integrating multiple applications, allowing them to share data and actions. New store and replay capabilities help developers evaluate the effectiveness of application builds, models and scenarios. Drools Workbench integration simplifies the modification of complex event processing rules. And new OLAP support for Druid makes it easier for users to analyze data in real time.
DataTorrent also introduced new applications for the financial services and retail industries as part of its AppFactory marketplace of big data streaming analytics use cases.
HCL began working with DataTorrent RTS in 2016, making the software part of the systems integrator's Enterprise Intelligence Hub unified architecture and implementing it as part of customers' data analytics and digital transformation projects, said Anand Birje, corporate vice president and global head of HCL's digital and analytics practice.
Birje, in an interview with CRN, said the expanded data visualization capabilities of the RTS 3.10 edition are key for HCL's work. He also praised additions to the Apoxi framework, which underlies RTS, and its tools for assembling and operating data-driven applications.
"We are familiar with the [3.10] release and our engineering and solutions teams have been working on a couple of deals with it," Birje said.
HCL, headquartered in Noida, India, formally became a DataTorrent partner late last year, Birje said. HCL also recently signed a partnership agreement with Oak Brook, Ill.-based Wavicle Data Solutions, a provider of big data, cloud and analytical solutions.
DataTorrent now has more than 20 partners including resellers, technology partners, ISVs, OEMs, systems integrators and consultants. Other partners include Trace3, MSys and Stratecha.