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A consistency/latency tradeoff arises as soon as a distributed storage systemreplicates data. For low latency, modern storage systems often settle for weakconsistency conditions, which provide little, or even worse, no guarantee fordata consistency. In this paper we propose the notion of almost strongconsistency as a better balance option for the consistency/latency tradeoff. Itprovides both deterministically bounded staleness of data versions for eachread and probabilistic quantification on the rate of "reading stale values",while achieving low latency. In the context of distributed storage systems, weinvestigate almost strong consistency in terms of 2-atomicity. Our 2AM(2-Atomicity Maintenance) algorithm completes both reads and writes in onecommunication round-trip, and guarantees that each read obtains the value ofwithin the latest 2 versions. To quantify the rate of "reading stale values",we decompose the so-called "old-new inversion" phenomenon into concurrencypatterns and read-write patterns, and propose a stochastic queueing model and a"timed balls-into-bins model" to analyze them, respectively. The theoreticalanalysis not only demonstrates that "old-new inversions" rarely occur asexpected, but also reveals that the read-write pattern dominates inguaranteeing such rare data inconsistencies. These are further confirmed by theexperimental results, showing that 2-atomicity is "good enough" in distributedstorage systems by achieving low latency, bounded staleness, and rare datainconsistencies.

Almost Strong Consistency: "Good Enough" in Distributed Storage Systems