How to use Persistent Memory in your Database

TL;DR

This paper empirically evaluates how different relational database engines perform with various configurations of persistent memory (PMEM), revealing insights into optimal usage and performance implications for databases leveraging new NVM hardware.

Contribution

It provides a comprehensive empirical analysis of PostgreSQL, MySQL, and SQLServer under different PMEM configurations and workloads, which was previously lacking.

Findings

PMEM as persistent storage generally speeds up queries.

Using PMEM in Memory mode offers no performance benefit.

Performance varies significantly with hardware configurations and query types.

Abstract

Persistent or Non Volatile Memory (PMEM or NVM) has recently become commercially available under several configurations with different purposes and goals. Despite the attention to the topic, we are not aware of a comprehensive empirical analysis of existing relational database engines under different PMEM configurations. Such a study is important to understand the performance implications of the various hardware configurations and how different DB engines can benefit from them. To this end, we analyze three different engines (PostgreSQL, MySQL, and SQLServer) under common workloads (TPC-C and TPC-H) with all possible PMEM configurations supported by Intel's Optane NVM devices (PMEM as persistent memory in AppDirect mode and PMEM as volatile memory in Memory mode). Our results paint a complex picture and are not always intuitive due to the many factors involved. Based on our findings, we provide insights on how the different engines behave with PMEM and which configurations and queries perform best. Our results show that using PMEM as persistent storage usually speeds up query execution, but with some caveats as the I/O path is not fully optimized. Additionally, using PMEM in Memory mode does not offer any performance advantage despite the larger volatile memory capacity. Through the extensive coverage of engines and parameters, we provide an important starting point for exploiting PMEM in databases and tuning relational engines to take advantage of this new technology.