Henrique Andrade did this work while at IBM Research. He is currently with Goldman Sachs in New York.
Evaluation of a high-volume, low-latency market data processing system implemented with IBM middleware†
Article first published online: 15 FEB 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Software: Practice and Experience
Volume 42, Issue 1, pages 37–56, January 2012
How to Cite
Park, Y., King, R., Nathan, S., Most, W. and Andrade, H. (2012), Evaluation of a high-volume, low-latency market data processing system implemented with IBM middleware. Softw: Pract. Exper., 42: 37–56. doi: 10.1002/spe.1047
- Issue published online: 27 DEC 2011
- Article first published online: 15 FEB 2011
- Manuscript Accepted: 21 NOV 2010
- Manuscript Revised: 29 OCT 2010
- Manuscript Received: 26 JUL 2010
- market data processing;
- IBM middleware;
- commodity hardware;
- performance optimizations
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. Copyright © 2011 John Wiley & Sons, Ltd.