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Large-scale information processing environments must rapidly search through massive streams of raw data to locate useful information. These data streams contain textual and numeric data items, and may be highly structured or mostly freeform text. This project aims to create a high performance and scalable engine for locating relevant content in data streams. Based on the J2EE Java Messaging Service (JMS), the content-based messaging (CBM) engine provides highly efficient message formatting and filtering. This paper describes the design of the CBM engine, and presents empirical results that compare the performance with a standard JMS to demonstrate the performance improvements that are achieved.