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It is challenging to process transactions in a timely fashion using fresh data, e.g., current stock prices, since database workloads may considerably vary due to dynamic data/resource contention. Further, transaction timeliness and data freshness requirements may compete for system resources. In this paper, we propose a novel feedback control model to support the desired data service delay by managing the size of the ready queue, which indicates the amount of the backlog in the database. We also propose a new self-adaptive update policy to adapt the freshness of cold data in a differentiated manner based on temporal data access and update patterns. Unlike most existing work on feedback control of real-time database (RTDB) performance, we actually implement and evaluate feedback control and database workload adaptation techniques in a real database testbed modeling stock trades. For performance …