A new approach to database management in solid-state drives

Korea, have developed a new approach to manage databases in solid state drives, providing marked performance improvements in read/write delays and offloading database computation tasks from CPUs to increase efficiency and reduce power consumption. In a recent study presented at the 2020 USENIX Annual Technical Conference, researchers from Daegu Gyeongbuk Institute of Science and Technology (DGIST), Korea, describe a new way of implementing a key–value store in solid state drives (SSDs), which offers many advantages over a more widely used method.

A key–value store (also known as key–value database) is a way of storing, managing, and retrieving data in the form of key–value pairs. The most common way to implement one is through the use of a hash function, an algorithm that can quickly match a given key with its associated stored data to achieve fast read/write access.One of the main problems of implementing a hash-based key–value store is that the random nature of the hash function occasionally leads to long delays (latency) in read/write operations. To solve this problem, the researchers from DGIST implemented a different paradigm, called "log-structured merge-tree (LSM)." This approach relies on ordering the data hierarchically, therefore putting an upper bound on the maximum latency.

In their implementation, nicknamed "PinK," they addressed the most serious limitations of LSM-based key–value stores for SSDs. With its optimized memory use, guaranteed maximum delays, and hardware accelerators for offloading certain sorting tasks from the CPU, PinK represents a novel and effective take on data storage for SSDs in data centers. So far, experimental results confirm the performance gains offered by this new implementation and highlight the potential of letting storage devices compute some operations by themselves.

https://techxplore.com/news/2020-08-approach-database-solid-state.html