High-performance stream processing is critical in many sense-and-respond application domainsfrom environmental monitoring to algorithmic trading. In this paper, we focus on language and runtime support for improving the performance of sense-and-respond applications in processing data from high-rate live streams. The central tenets of this work are the programming model, the workload splitting mechanisms, the code generation framework, and the underlying System S middleware and Spade programming model. We demonstrate considerable scalability behavior coupled with low processing latency in a real-world financial trading application. © 2010 Elsevier Inc. All rights reserved.