Wireless sensor networks are rapidly finding their way through a plethora of new applications like precision farming and forestry, with increasing network scale, system complexity, and data rate. While scalable MAC and routing protocols for sensor networks have been well addressed in recent years, the scalability of the back-end storage architecture has been largely overlooked. As a result, current storage and retrieval architectures usually lead to an excessive I/O cost when it comes to improving the scalability and responsiveness of the system. In this paper, we present a scalable backend storage and retrieval architecture to support very large volumes of realtime measurements from wireless sensor networks. In particular, our contribution provides: (i) a database partitioning and structuring scheme coupled with a doublebuffering technique to reduce the end-to-end delay while minimizing the processing power, and (ii) an optimized historical measurement data query format tailored for...