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Strictly serializable (linearizable) services appear to execute transactions (operations) sequentially, in an order consistent with real time. This restricts a transaction's (operation's) possible return values and in turn, simplifies application programming. In exchange, strictly serializable (linearizable) services perform worse than those with weaker consistency. But switching to such services can break applications. This work introduces two new consistency models to ease this trade-off: regular sequential serializability (RSS) and regular sequential consistency (RSC). They are just as strong for applications: we prove any application invariant that holds when using a strictly serializable (linearizable) service also holds when using an RSS (RSC) service. Yet they relax the constraints on services---they allow new, better-performing designs. To demonstrate this, we design, implement, and evaluate variants of two systems, Spanner and Gryff, relaxing their consistency to RSS and RSC, respectively. The new variants achieve better read-only transaction and read tail latency than their counterparts. 

Linearizability reduces the complexity of building correct applications. However, there is a tradeoff between using linearizability for geo-replicated storage and low tail latency. Traditional approaches use consensus to implement linearizable replicated state machines, but consensus is inefficient for workloads composed mostly of reads and writes. We present the design, implementation, and evaluation of Gryff, a system that offers linearizability and low tail latency by unifying consensus with shared registers. Gryff introduces carstamps to correctly order reads and writes without incurring unnecessary constraints that are required when ordering stronger synchronization primitives. Our evaluation shows that Gryff’s combination of an optimized shared register protocol with EPaxos allows it to provide lower service-level latency than EPaxos or MultiPaxos due to its lower tail latency for reads. 

This paper presents the design and implementation of Obladi, the first system to provide ACID transactions while also hiding access patterns. Obladi uses as its building block oblivious RAM, but turns the demands of supporting transac- tions into a performance opportunity. By executing transac- tions within epochs and delaying commit decisions until an epoch ends, Obladi reduces the amortized bandwidth costs of oblivious storage and increases overall system through- put. These performance gains, combined with new oblivious mechanisms for concurrency control and recovery, allow Obladi to execute OLTP workloads with reasonable through- put: it comes within 5× to 12× of a non-oblivious baseline on the TPC-C, SmallBank, and FreeHealth applications. Latency overheads, however, are higher (70× on TPC-C).