Kite: efficient and available release consistency for the datacenter

Key-Value Stores (KVSs) came into prominence as highly-available, eventually consistent (EC), "NoSQL" Databases, but have quickly transformed into general-purpose, programmable storage systems. Thus, EC, while relevant, is no longer sufficient. Complying with the emerging requirements for stronger consistency, researchers have proposed KVSs with multiple consistency levels (MCL) that expose the consistency/performance trade-off to the programmer. We argue that this approach falls short in both programmability and performance. For instance, the MCL APIs proposed thus far, fail to capture the ordering relationship between strongly- and weakly-consistent accesses that naturally occur in programs. Taking inspiration from shared memory, we advocate Release Consistency (RC) for KVSs. We argue that RC's onesided barriers are ideal for capturing the ordering relationship between synchronization and non-synchronization accesses while enabling high-performance. We present Kite, the first highly-available, replicated KVS that offers a linearizable variant of RC for the asynchronous setting with individual process and network failures. Kite enforces RC barriers through a novel fast/slow path mechanism that leverages the absence of failures in the typical case to maximize performance while relying on the slow path for progress. Our evaluation shows that the RDMA-enabled and heavily-multithreaded Kite achieves orders of magnitude better performance than Derecho (a state-of-the-art RDMA-enabled state machine replication system) and significantly outperforms ZAB (the protocol at the heart of Zookeeper). We demonstrate the efficacy of Kite by porting three lock-free shared memory data structures, and showing that Kite outperforms the competition.