SplinterDB - Closing the Bandwidth Gap for NVMe Key-Value Stores

Explore a conference talk that introduces SplinterDB, a novel key-value store designed specifically for NVMe solid state drives. Learn about the STBε-tree data structure, which improves I/O and CPU concurrency while reducing write amplification without compromising query performance. Discover how SplinterDB combines elements from log-structured merge trees and Bε-trees to optimize compaction and minimize CPU costs. Examine the highly concurrent memtable and cache design that reduces cache misses. Compare SplinterDB's performance to RocksDB, a leading key-value store, and understand how it achieves 6-10x faster insertions, 2-2.6x quicker point queries, and a 2x reduction in write amplification. Gain insights into the technical aspects of SplinterDB's architecture and its potential impact on modern storage systems.

Introduction
Overview
Performance
Size 2Bepsilon tree
Size 3Bepsilon tree
Size 4Bepsilon tree
Flush Compact
Conclusion