A stock market data processing system that can handle high data volumes at low latencies is critical to market makers. Such systems play a critical role in algorithmic trading, risk analysis, market surveillance, and many other related areas. The current systems tend to use specialized software and custom processors. We show that such a system can be built with general-purpose middleware and run on commodity hardware. The middleware we use is IBM System S which includes transport technology from IBM WebSphere MQ Low Latency Messaging (LLM). Our performance evaluation consists of two parts. First, we determined the effectiveness of each system optimization that the hardware and software infrastructure makes available. These optimizations were implemented at all software levels-application, middleware, and operating system. Second, we evaluated our system on different hardware platforms. © 2011 John Wiley & Sons, Ltd.