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.

中文翻译：

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持久键值存储的功耗和性能分析

随着当前的数据增长速度，由于 CPU 功率和能源限制，处理需求变得难以满足。数据服务系统，尤其是持久化键值存储，已经成为数据中心数据处理栈的重要组成部分，为应用和服务提供海量数据的访问。键值存储表现出高 CPU 和 I/O 开销，因为它们不断需要重新组织设备上的数据。在本文中，我们检查了四个不同代和不同 CPU 架构的服务器上的两个键值存储的效率。我们使用 RocksDB，这是一种广泛部署的键值，例如在 Facebook 中，以及 Kreon，一种旨在减少 CPU 开销的研究键值存储。我们在基于 ARM 的微服务器和三代不同的 x86 服务器上评估它们的行为和开销。我们的研究结果表明，微服务器在 0.68-3.6 倍的范围内具有更好的电源效率，并且具有可比的尾部延迟。