English

Power and Performance Analysis of Persistent Key-Value Stores

Distributed, Parallel, and Cluster Computing 2020-09-01 v1 Performance

Abstract

With the current rate of data growth, processing needs are becoming difficult to fulfill due to CPU power and energy limitations. Data serving systems and especially persistent key-value stores have become a substantial part of data processing stacks in the data center, providing access to massive amounts of data for applications and services. Key-value stores exhibit high CPU and I/O overheads because of their constant need to reorganize data on the devices. In this paper, we examine the efficiency of two key-value stores on four servers of different generations and with different CPU architectures. We use RocksDB, a key-value that is deployed widely, e.g. in Facebook, and Kreon, a research key-value store that has been designed to reduce CPU overhead. We evaluate their behavior and overheads on an ARM-based microserver and three different generations of x86 servers. Our findings show that microservers have better power efficiency in the range of 0.68-3.6x with a comparable tail latency.

Keywords

Cite

@article{arxiv.2008.13402,
  title  = {Power and Performance Analysis of Persistent Key-Value Stores},
  author = {Stella Mikrou and Anastasios Papagiannis and Giorgos Saloustros and Manolis Marazakis and Angelos Bilas},
  journal= {arXiv preprint arXiv:2008.13402},
  year   = {2020}
}
R2 v1 2026-06-23T18:12:06.247Z