  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 KV
stores has become even more complex. More recent KV-store designs target fast
storage devices, such as SSDs and NVM. Most of these designs aim to reduce
amplification during data reorganization by taking advantage of device
characteristics. However, until today most analysis of KV-store designs is
experimental and limited to specific design points. This makes it difficult to
compare tradeoffs across different designs, find optimal configurations and
guide future KV-store design. In this paper, we introduce the Variable
Amplification- Throughput analysis (VAT) to calculate insert-path amplification
and its impact on multi-level KV-store performance.We use VAT to express the
behavior of several existing design points and to explore tradeoffs that are
not possible or easy to measure experimentally. VAT indicates that by inserting
randomness in the insert-path, KV stores can reduce amplification by more than
10x for fast storage devices. Techniques, such as key-value separation and
tiering compaction, reduce amplification by 10x and 5x, respectively.
Additionally, VAT predicts that the advancements in device technology towards
NVM, reduces the benefits from both using key-value separation and tiering.
