# Sherman: A Write-Optimized Distributed B+Tree Index on Disaggregated Memory

arXiv: https://arxiv.org/abs/2112.07320 · HTML: https://mlsanity.com/paper/2112.07320/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Dec 2021.

## Built on by (most cited first, 1 of 1)

- [Towards Efficient Key-Value Cache Management for Prefix Prefilling in LLM Inference](https://mlsanity.com/paper/2505.21919/) (2025)

## Abstract (arXiv)

Memory disaggregation architecture physically separates CPU and memory into independent components, which are connected via high-speed RDMA networks, greatly improving resource utilization of databases. However, such an architecture poses unique challenges to data indexing in databases due to limited RDMA semantics and near-zero computation power at memory-side. Existing indexes supporting disaggregated memory either suffer from low write performance, or require hardware modification. This paper presents Sherman, a write-optimized distributed B+Tree index on disaggregated memory that delivers high performance with commodity RDMA NICs. Sherman combines RDMA hardware features and RDMA-friendly software techniques to boost index write performance from three angles. First, to reduce round trips, Sherman coalesces dependent RDMA commands by leveraging in-order delivery property of RDMA. Second, to accelerate concurrent accesses, Sherman introduces a hierarchical lock that exploits on-chip memory of RDMA NICs. Finally, to mitigate write amplification, Sherman tailors the data structure layout of B+Tree with a two-level version mechanism. Our evaluation shows that, Sherman is one order of magnitude faster in terms of both throughput and 99th percentile latency on typical write-intensive workloads, compared with state-of-the-art designs.