As the demand for real-time data services (e.g., e-commerce or on line auctions) increases, it is desired for a real-time database to increase the timely throughput-the amount of data processed in a timely manner. As the timely throughput of a centralized real-time database is limited, it is desired to federate a set of real-time databases to increases the timely throughput. However, related work on distributed real-time databases is scarce. Most existing approaches are highly complex, incurring non-trivial overheads. Neither are they implemented in a real database system. To address the problem, we design a new system architecture for federated real-time data services and develop efficient approaches for load sharing among a set of clustered databases. To support the desired data service delay even in the presence of dynamic workloads, each individual database employs a single-input single-output (SISO) feedback admission control scheme. Based on the admission control signals collected from the individual databases, cluster-wide load sharing is performed to enhance the total timely throughput by fully utilizing the federated databases, while avoiding to overload them. We have implemented and evaluated the performance of our approach by extending the Oracle Berkeley DB. Our system significantly enhances the timely data throughput compared to a single centralized system, while effectively dealing with emulated partial unavailability of a set of federated databases.