Product Overview

SAS Event Stream Processing enables programmers to build applications that can quickly process and analyze a large number of continuously flowing events. Programmers can build applications using the XML Layer or the C++ Modeling API that are included with the product. Event streams are published in applications using the C, JAVA, or Python publish/subscribe APIs, connector classes, adapter executables, Streamviewer, or SAS Event Stream Processing Studio.

Event stream processing engines with dedicated thread pools can be embedded within new or existing applications. The XML client can be used to feed event stream processing engine definitions (called projects) into an event stream processing XML server.

Event stream processing applications typically perform real-time analytics on streams of events. These streams are continuously published into an event stream processing engine. Typical use cases for event stream processing include but are not limited to the following:

• capital markets trading systems
• fraud detection and prevention
• sensor data monitoring and management
• cyber security analytics
• operational systems monitoring and management
• personalized marketing

Event stream processing enables the user to analyze continuously flowing data over long periods of time where low-latency incremental results are important.