Rearchitecting In-Memory Object Stores for Low Latency
Summary: Lightning rearchitects in-memory object stores around shared-memory direct access, eliminating IPC for single-user, multi-process AI workloads while preserving isolation via MPK, transaction logging, and formal verification. Delivers up to 9× NOSQL speedups and 40% higher RL throughput. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Danyang Zhuo (Duke University)
- 2. Kaiyuan Zhang (University of Washington)
- 3. Zhuohan Li (University of California Berkeley)
- 4. Siyuan Zhuang (University of California Berkeley)
- 5. Stephanie Wang (University of California Berkeley)
- 6. Ang Chen (Rice University)
- 7. Ion Stoica (University of California Berkeley)
BibTeX Citation
@article{zhuo_vldb22,
title = {{Rearchitecting In-Memory Object Stores for Low Latency}},
author = {Zhuo, Danyang and Zhang, Kaiyuan and Li, Zhuohan and Zhuang, Siyuan and Wang, Stephanie and Chen, Ang and Stoica, Ion},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {3},
pages = {555--568},
doi = {10.14778/3494124.3494138},
url = {https://doi.org/10.14778/3494124.3494138},
year = {2022}
}
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,498 | Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores | 2015 | VLDB | 8.5016595e-05 |
| 5,542 | Put an Elephant into a Fridge: Optimizing Cache Efficiency for In-memory Key-value Stores | 2020 | VLDB | 6.180117e-05 |
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