An Analysis of Ethereum Workloads from a Key-Value Storage Perspective

Abstract

Blockchains have revolutionized trust and transparency in distributed systems, yet their heavy reliance on key-value (KV) storage for managing immutable, rapidly growing data leads to performance bottlenecks due to I/O inefficiencies. In this paper, we analyze Ethereum’s storage workload traces, with billions of KV operations, across four dimensions: storage overhead, KV operation distributions, read correlations, and update correlations. Our study reveals 11 key findings and provides suggestions on the design and optimization of blockchain storage.