Aleri enhances event processing technology

Source: Aleri

Aleri, the leading provider of enterprise-class complex event processing technology, today announced the unveiling of new key features now available on the Aleri Streaming Platform.

The Aleri Streaming Platform was designed from the ground up to provide the most robust architecture available allowing for rapid analysis and response to high-volume, high-speed data within the most demanding environments. New features including Dynamic Data Models, the Aleri Dashboard, and broader operating system compatibility extend the Platform's architecture to further increase efficiency and ease of use.

Aleri's Dynamic Data Models facilitate non-stop operation of the Aleri Streaming Platform, allowing customers to easily and quickly change and enhance event processing applications without interruption. Customers can now add new event processing rules, create new derived streams, change formulas and parameters, or shut down specific rules, all without interrupting the processing of inputs and concurrent running rules. The Aleri Dashboard provides customers with a customizable, graphically-rich user interface to display data and graphs that update in real-time. Additionally, the Aleri Streaming Platform is now even more versatile with compatibility on more operating systems, including Linux, Solaris and Microsoft Windows.

"Our event processing technology has been deployed in some of the most demanding
environments at many of the world's largest banks," said Don DeLoach, president and CEO of Aleri. "We are continuously enhancing our event processing technology to meet and exceed the needs of our customers. These enhancements build on our industrial strength Platform to address the true needs of today's enterprise."

The Aleri Streaming Platform is specifically designed for enterprise-class deployments. It combines data persistence, high-performance processing of large data sets, highavailability configurations, programmable stream operators and built-in security features to enable companies to quickly and cost-effectively build applications that can successfully analyze and act on large amounts of fast moving data.

Comments: (0)