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In this paper, we show that key-value stores backed by an LSM-tree exhibit an intrinsic trade-off between lookup cost, update cost, and main memory footprint, yet all existing designs expose a suboptimal and difficult to tune trade-off among these metrics. We pinpoint the problem to the fact that all modern key-value stores suboptimally co-tune the merge policy, the buffer size, and the Bloom filters' false positive rates in each level.
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Niv Dayan
University of Toronto
Manos Athanassoulis
Boston University
Stratos Idreos
Harvard University
Harvard University
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Dayan et al. (Tue,) studied this question.
synapsesocial.com/papers/69c9105f37154e59f407887e — DOI: https://doi.org/10.1145/3035918.3064054