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Over the past years, there has been an increasing number of key-value (KV)store designs, each optimizing for a different set of requirements.Furthermore, with the advancements of storage technology the design space of KVstores has become even more complex. More recent KV-store designs target faststorage devices, such as SSDs and NVM. Most of these designs aim to reduceamplification during data reorganization by taking advantage of devicecharacteristics. However, until today most analysis of KV-store designs isexperimental and limited to specific design points. This makes it difficult tocompare tradeoffs across different designs, find optimal configurations andguide future KV-store design. In this paper, we introduce the VariableAmplification- Throughput analysis (VAT) to calculate insert-path amplificationand its impact on multi-level KV-store performance.We use VAT to express thebehavior of several existing design points and to explore tradeoffs that arenot possible or easy to measure experimentally. VAT indicates that by insertingrandomness in the insert-path, KV stores can reduce amplification by more than10x for fast storage devices. Techniques, such as key-value separation andtiering compaction, reduce amplification by 10x and 5x, respectively.Additionally, VAT predicts that the advancements in device technology towardsNVM, reduces the benefits from both using key-value separation and tiering.

VAT: Asymptotic Cost Analysis for Multi-Level Key-Value Stores