SAN JOSE, Calif.--(BUSINESS WIRE)--DataTorrent, a big data analytics applications company and market leader in real-time, data-in-motion stream processing, today announced a significant update to its DataTorrent Real-time Streaming (RTS) platform for swiftly building, deploying, and operating real-time streaming data applications. DataTorrent RTS 3.10 provides new capabilities that make it easier than ever for customers to explore, analyze, and visualize trends in data as it is created and to build new kinds of production-ready applications that drive their business forward.
“Companies everywhere are keenly aware of the need to gain insight from data to become more customer-centric, improve operational performance, and create new revenue streams,” said Guy Churchward, CEO of DataTorrent. “Today’s updates are not only designed to help organizations make better decisions faster, but they are part of our strategy to fundamentally change the way big data applications are designed, deployed, and managed.”
DataTorrent’s RTS platform provides all the functionality a business needs to develop and deliver best-in-class, fast data applications. This platform is supported by DataTorrent’s RTS Apoxi™ framework, which provides the tools required to assemble, manage, and operate fast data applications on any infrastructure, enabling customers to harness the best of open source innovation while achieving operational readiness at any scale. Apoxi is a framework that uniquely binds components together to create optimized, pre-built applications and can also integrate independent applications to allow them to operate as one.
The key new features in RTS 3.10 include:
- Support for OLAP with Druid provides customers with the ability to slice and dice data in real-time to get the information needed to compute and compare it to historical trends. This capability is delivered as a pre-built component that integrates Apex, Druid, and SuperSet for real-time BI dashboards and visualizations.
- Expanded support for machine learning and AI helps customers capitalize on the value from the latest innovations in data science. This includes native support for the delivery of analytical logic using machine scoring models written in Python or Predictive Model Markup Language (PMML).
- Store and Replay helps customers push to production with confidence. Customers can record and replay data from a point in time to evaluate the effectiveness of builds, models, and scenarios before they are put into production, removing the guesswork about what outcomes will occur.
- Drools Workbench integration makes it easier to modify complex event processing (CEP) rules and push new rules to production. The workbench enables customers to import data schema and visually edit and manage complex rules easily by using an intuitive graphical user interface.
- Application Backplane enables multiple applications to be simply and consistently integrated in order to share insights and actions. Combining numerous applications in real-time can result in significantly better outcomes, while still enabling separately managed applications to remain independent and benefit from a network-effect.
“Business intelligence and analytics are a top IT priority for enterprises in 2018 and a stepping stone to advanced capabilities like machine learning and artificial intelligence,” said Matt Aslett, research director for Data Platforms and Analytics, 451 Research. “Yet, while being able to make critical business decisions as soon as possible following an event is a big competitive advantage, many enterprises are still struggling to get the basics right.”
Expanding on its commitment to deliver pre-built, enterprise-hardened applications via its DataTorrent RTS AppFactory, DataTorrent is introducing a set of new applications focused on the financial services and retail verticals. AppFactory is DataTorrent’s marketplace for big data streaming analytics use cases, reference architectures, and downloadable applications arranged by industry or technology. The new additions include:
- Omni-channel Payment Fraud Prevention. The newest version of DataTorrent’s Omni-channel Payment Fraud Prevention application integrates with the Druid OLAP component for real-time online analytical processing and enhanced historical trend analysis. This latest application also includes a reference architecture for integration with a variety of machine-trained analytical models for enhanced fraud prevention.
- Online Account Takeover Prevention. A reference application that enables customers to prevent online account takeover and fraud by processing, enriching, analyzing, and acting on multiple streams of account event information in real-time.
- Retail Recommender. Real-time, personalized product and service recommendations drive additional revenue for retail and ecommerce companies. DataTorrent’s Retail Recommender provides a reference architecture that produces product recommendations in real-time by operationalizing the latest innovations in machine-learning.
For more details about RTS 3.10, visit https://www.datatorrent.com/blog/.
DataTorrent enables organizations to achieve better business outcomes by delivering enterprise-hardened, big data analytics applications built on open source components using the latest innovations in operationalization, data science, and machine learning. DataTorrent improves time to value and lowers total cost of ownership through our combination of pre-built, big data application pipelines and our industry-proven expertise in deploying highly scalable, fault tolerant data-in-motion analytics applications for the fastest insight and action. For more information, visit www.datatorrent.com or follow us on Twitter @datatorrent.