From Flash to 3D XPoint: Performance Bottlenecks and Potentials in RocksDB with Storage Evolution Yichen Jia Feng Chen Computer Science and Engineering Computer Science and Engineering Louisiana State University Louisiana State University
[email protected] [email protected] Abstract—Storage technologies have undergone continuous much lower latency and higher throughput. Most importantly, innovations in the past decade. The latest technical advance- 3D XPoint SSD significantly alleviates many long-existing ment in this domain is 3D XPoint memory. As a type of Non- concerns on flash SSDs, such as the read-write speed disparity, volatile Memory (NVM), 3D XPoint memory promises great improvement in performance, density, and endurance over NAND slow random write, and endurance problems [26], [42]. Thus flash memory. Compared to flash based SSDs, 3D XPoint based 3D XPoint SSD is widely regarded as a pivotal technology for SSDs, such as Intel’s Optane SSD, can deliver unprecedented low building the next-generation storage system in the future. latency and high throughput. These properties are particularly On the software side, in order to accelerate I/O-intensive appealing to I/O intensive applications. Key-value store is such services in data centers, RocksDB [11], which is the state- an important application in data center systems. This paper presents the first, in-depth performance study of-art Log-structured Merge tree (LSM-tree) based key-value on the impact of the aforesaid storage hardware evolution store, has been widely used in various major data storage to RocksDB, a highly popular key-value store based on Log- and processing systems, such as graph databases [8], stream structured Merge tree (LSM-tree).