Scaling Replicated State Machines with Compartmentalization
Summary: Introduces compartmentalization as the first comprehensive method to decouple and independently scale bottlenecks in replicated state machines (e.g., MultiPaxos, Raft). Achieves 6× write-only and 16× mixed throughput without specialized hardware; a protocol-agnostic technique that can be adopted incrementally by existing protocols. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Michael Whittaker (University of California Berkeley)
- 2. Ailidani Ailijiang (Microsoft)
- 3. Aleksey Charapko (University of New Hampshire)
- 4. Murat Demirbas (State University of New York at Buffalo)
- 5. Neil Giridharan (University of California Berkeley)
- 6. Joseph M. Hellerstein (University of California Berkeley)
- 7. Heidi Howard (University of Cambridge)
- 8. Ion Stoica (University of California Berkeley)
- 9. Adriana Szekeres (VMware)
BibTeX Citation
@article{whittaker_vldb21,
title = {{Scaling Replicated State Machines with Compartmentalization}},
author = {Whittaker, Michael and Ailijiang, Ailidani and Charapko, Aleksey and Demirbas, Murat and Giridharan, Neil and Hellerstein, Joseph M. and Howard, Heidi and Stoica, Ion and Szekeres, Adriana},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {11},
pages = {2203--2215},
doi = {10.14778/3476249.3476273},
url = {https://doi.org/10.14778/3476249.3476273},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,741 | PigPaxos: Devouring the Communication Bottlenecks in Distributed Consensus | 2021 | SIGMOD | 6.5269811e-05 |
| 7,916 | Nezha: Deployable and High-Performance Consensus Using Synchronized Clocks | 2023 | VLDB | 5.5181056e-05 |
| 8,239 | In-Network Leaderless Replication for Distributed Data Stores | 2022 | VLDB | 5.4595803e-05 |
| 9,341 | Optimizing Distributed Protocols with Query Rewrites | 2024 | SIGMOD | 5.2859171e-05 |
| 10,826 | FLEET: High-Performance Durable Replicated State Machines using Scattered and Coordinated Log Entries | 2025 | VLDB | 5.093636e-05 |
| 11,359 | FlexiRaft: Flexible Quorums with Raft | 2023 | CIDR | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 57 | Calvin: Fast Distributed Transactions for Partitioned Database Systems | 2012 | SIGMOD | 0.00040139242 |
| 208 | CockroachDB: The Resilient Geo-Distributed SQL Database | 2020 | SIGMOD | 0.00024968157 |
| 3,666 | Harmonia: Near-Linear Scalability for Replicated Storage with In-Network Conflict Detection | 2020 | VLDB | 7.2142119e-05 |
| 4,523 | Tunable Consistency in MongoDB | 2019 | VLDB | 6.6463056e-05 |
| 4,741 | PigPaxos: Devouring the Communication Bottlenecks in Distributed Consensus | 2021 | SIGMOD | 6.5269811e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 7,534 | A Fault-Tolerant Commit Protocol for Replicated Databases | 1992 | PODS |
| 2 | 4,829 | Strong consistency is not hard to get: Two-Phase Locking and Two-Phase Commit on Thousands of Cores | 2019 | VLDB |
| 3 | 5,910 | Replication, Consistency, and Practicality: Are These Mutually Exclusive? | 1998 | SIGMOD |
| 4 | 6,296 | Dissecting the Performance of Strongly-Consistent Replication Protocols | 2019 | SIGMOD |
| 5 | 1,637 | On the Design and Scalability of Distributed Shared-Data Databases | 2015 | SIGMOD |
| 6 | 5,065 | Serializability, not Serial: Concurrency Control and Availability in Multi-Datacenter Datastores | 2012 | VLDB |
| 7 | 4,741 | PigPaxos: Devouring the Communication Bottlenecks in Distributed Consensus | 2021 | SIGMOD |
| 8 | 2,497 | Low-Latency Multi-Datacenter Databases using Replicated Commit | 2013 | VLDB |
| 9 | 9,341 | Optimizing Distributed Protocols with Query Rewrites | 2024 | SIGMOD |
| 10 | 10,874 | HoliPaxos: Towards More Predictable Performance in State Machine Replication | 2025 | VLDB |