TrafficDB
Ricardo Fernandes, Piotr Zaczkowski, Bernd Göttler, Conor Ettinoffe, Anis Moussa · Proceedings of the VLDB Endowment · 2016
HERE's traffic-aware services enable route planning and traffic visualisation on web, mobile and connected car applications. These services process thousands of requests per second and require efficient ways to access the information needed to provide a timely response to end-users. The characteristics of road traffic information and these traffic-aware services require storage solutions with specific performance features. A route planning application utilising traffic congestion information to calculate the optimal route from an origin to a destination might hit a database with millions of queries per second. However, existing storage solutions are not prepared to handle such volumes of concurrent read operations, as well as to provide the desired vertical scalability. This paper presents TrafficDB, a shared-memory data store, designed to provide high rates of read operations, enabling applications to directly access the data from memory. Our evaluation demonstrates that TrafficDB handles millions of read operations and provides near-linear scalability on multi-core machines, where additional processes can be spawned to increase the systems' throughput without a noticeable impact on the latency of querying the data store. The paper concludes with a description of how TrafficDB improved the performance of our traffic-aware services running in production.