In large federations of autonomous database systems, automatic distribution of the query workload to those systems is a critical issue. We examine this problem under the perspective of microeconomics theory and show how the latter can be used to construct an efficient decentralized mechanism that maximizes system throughput. In particular, we introduce a solution that is based on the notion of query markets. We examine the properties of these markets and show that they result in Pareto-optimal allocations of resources to queries. An extensive set of experiments with both a simulator and an actual implementation on top of a commercial DBMS demonstrate significant improvements in the overall system throughput when our technique is used.