The demand for real-time database services has been increasing recently. Examples include sensor data fusion, decision support, web information services, and online trading. In these applications, it is desirable to execute transactions within their deadlines using temporally consistent data. Due to the high service demand, real-time databases can be overloaded. As a result, many transactions may miss their deadlines, or data temporal consistency constraints can be violated. To address these problems, we present a QoS management scheme to support guarantees on deadline miss ratio and data freshness (temporal consistency) even in the presence of unpredictable workloads and data access patterns. Using our approach, admitted user transactions can be processed in time using fresh data. A simulation study shows that our QoS-sensitive approach can achieve a significant performance improvement, in terms of deadline miss ratio and data freshness, compared to several baseline approaches. Furthermore, our approach shows a comparable performance to the theoretical oracle that is privileged by a complete future knowledge of data accesses.