research-article

ScaleStore: A Fast and Cost-Efficient Storage Engine using DRAM, NVMe, and RDMA

Authors:

Tobias Ziegler,

Carsten Binnig,

Viktor LeisAuthors Info & Claims

SIGMOD '22: Proceedings of the 2022 International Conference on Management of Data

Pages 685 - 699

https://doi.org/10.1145/3514221.3526187

Published: 11 June 2022 Publication History

Abstract

In this paper, we propose ScaleStore, a novel distributed storage engine that exploits DRAM caching, NVMe storage, and RDMA networking to achieve high performance, cost-efficiency, and scalability at the same time. Using low latency RDMA messages, ScaleStore implements a transparent memory abstraction that provides access to the aggregated DRAM memory and NVMe storage of all nodes. In contrast to existing distributed RDMA designs such as NAM-DB or FaRM, ScaleStore stores cold data on NVMe SSDs (flash), lowering the overall hardware cost significantly. The core of ScaleStore is a distributed caching strategy that dynamically decides which data to keep in memory (and which on SSDs) based on the workload. The caching protocol also provides strong consistency in the presence of concurrent data modifications. Our evaluation shows that ScaleStore achieves high performance for various types of workloads (read/write-dominated, uniform/skewed) even when the data size is larger than the aggregated memory of all nodes. We further show that ScaleStore can efficiently handle dynamic workload changes and supports elasticity.

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Cited By

Jasny MZiegler TBinnig C(2025)Scalable Data Management on Next-Generation Data Center NetworksScalable Data Management for Future Hardware10.1007/978-3-031-74097-8_8(199-221)Online publication date: 24-Jan-2025
https://doi.org/10.1007/978-3-031-74097-8_8
Wang HOu JZhao MQiu SJiao YWang YMao QYang ZLiu YZhang JHu JZhang JLiu JChen JShen YCao LZhang HLi HLi MMa YZhang LLiu JZhang GLiu FChen J(2024)LavaStore: ByteDance's Purpose-Built, High-Performance, Cost-Effective Local Storage Engine for Cloud ServicesProceedings of the VLDB Endowment10.14778/3685800.368580717:12(3799-3812)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.14778/3685800.3685807
Lu BHuang KLiang CWang TLo E(2024)DEX: Scalable Range Indexing on Disaggregated MemoryProceedings of the VLDB Endowment10.14778/3675034.367505017:10(2603-2616)Online publication date: 6-Aug-2024
https://dl.acm.org/doi/10.14778/3675034.3675050
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Index Terms

ScaleStore: A Fast and Cost-Efficient Storage Engine using DRAM, NVMe, and RDMA
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. DBMS engine architectures
      2. Parallel and distributed DBMSs

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cover image ACM Conferences

SIGMOD '22: Proceedings of the 2022 International Conference on Management of Data

June 2022

2597 pages

ISBN:9781450392495

DOI:10.1145/3514221

General Chair:
Zachary Ives
University of Pennsylvania (USA)
,
Program Chairs:
Angela Bonifati
Lyon 1 University (France)
,
Amr El Abbadi
University of California, Santa Barbara (USA)

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Published: 11 June 2022

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SIGMOD/PODS '22: International Conference on Management of Data

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Cited By

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https://doi.org/10.1007/978-3-031-74097-8_8
Wang HOu JZhao MQiu SJiao YWang YMao QYang ZLiu YZhang JHu JZhang JLiu JChen JShen YCao LZhang HLi HLi MMa YZhang LLiu JZhang GLiu FChen J(2024)LavaStore: ByteDance's Purpose-Built, High-Performance, Cost-Effective Local Storage Engine for Cloud ServicesProceedings of the VLDB Endowment10.14778/3685800.368580717:12(3799-3812)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.14778/3685800.3685807
Lu BHuang KLiang CWang TLo E(2024)DEX: Scalable Range Indexing on Disaggregated MemoryProceedings of the VLDB Endowment10.14778/3675034.367505017:10(2603-2616)Online publication date: 6-Aug-2024
https://dl.acm.org/doi/10.14778/3675034.3675050
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