— Distributed hash tables (DHTs) provide efficient data naming and location with simple hash-table-like primitives, upon which sophisticated distributed applications can be built. DHT users provide free but unstable peer-to-peer (P2P) capacity. With stable DHT nodes being relatively scarce, a DHT can either rely on a small set of stable nodes with limited collective capacity, or a larger set of potentially less stable nodes and suffer maintenance and data redundancy overhead. In this paper, we provide an analytical model that captures the tradeoff between the stability and the scalability in DHT-based P2P systems. We use the model to demonstrate that the DHT throughput can be optimized through careful engineering of DHT node selection and data redundancy parameters.