Massive storage systems typically replicate and partition data over many potentially-faulty components to provide both reliability and scalability. Yet many commercially-deployed systems, especially those designed for interactive use by customers, sacrifice stronger consistency properties in the desire for greater availability and higher throughput. This paper describes the design, implementation, and evaluation of CRAQ, a distributed object-storage system that challenges this inflexible tradeoff. Our basic approach, an improvement on Chain Replication, maintains strong consistency while greatly improving read throughput. By distributing load across all object replicas, CRAQ scales linearly with chain size without increasing consistency coordination. At the same time, it exposes non-committed operations for weaker consistency guarantees when this suffices for some applications, which is especially useful under periods of high system churn. This paper explores additional design and implementation considerations for geo-replicated CRAQ storage across multiple datacenters to provide locality-optimized operations. We also discuss multi-object atomic updates and multicast optimizations for large-object updates.