VLDB2022

Tair-PMem: a Fully Durable Non-Volatile Memory Database

Caixin Gong, Chengjin Tian, Zhengheng Wang, Sheng Wang, Xiyu Wang, Qiulei Fu, Wu Qin, Qian Long, Rui Chen, Jiang Qi, Ruo Wang, Guoyun Zhu, Chenghu Yang, Wei Zhang, Feifei Li

被引用 15 次

摘要

In-memory databases (IMDBs) have been the backbone of modern systems that demand high throughput and low latency. Because of the cost and volatility of DRAM, IMDBs become incompetent when dealing with workloads that require large data volume and strict durability. The emergence of non-volatile memory (NVM) brings new opportunities for IMDBs to tackle this situation. However, it is non-trivial to build an NVM-based IMDB, due to performance degradation, NVM programming complexity, and other challenges. In this paper, we present Tair-PMem, an NVM-based enterprisestrength database atop Redis, the most popular IMDB. Tair-PMem adopts a well-controlled data layout and a log-as-user-data design to mitigate NVM overheads. It eases the NVM programming complexity by providing a hybrid memory programming toolkit. To better leverage the enterprise-strength features and implementations from Redis, Tair-PMem retrots it in a less intrusive way to achieve full compatibility and stability, while retaining its advanced features. With all of the above techniques elaborately implemented, Tair-PMem satises full durability, high throughput, and low latency at the same time. Tair-PMem has now been publicly available as a cloud service on Alibaba Cloud. To the best of our knowledge, Tair-PMem is the rst cloud service that makes good use of the persistence capability of NVM.