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LSM-Trees and B-Trees: The Best of Both Worlds

Published: 25 June 2019 Publication History

Abstract

LSM-Trees and B-Trees are the two primary data structures used as storage engines in modern key-value (KV) stores. These two structures are optimal for different workloads; LSM-Trees perform better on update queries, whereas B-Trees are preferable for short range lookups. KV stores today use one or the other. However, for modern applications with increasingly diverse workloads, limiting KV stores to utilize only one of the two designs leads to a significant loss in performance. We propose a novel method of online transitioning a KV store from an LSM-Tree to a B-Tree and vice versa. This allows KV stores to smoothly adapt to changing workloads and use the optimal data structure as the workload changes.

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Cited By

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  • (2024)BushStore: Efficient B+Tree Group Indexing for LSM-Tree in Non-Volatile Memory2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00316(4127-4139)Online publication date: 13-May-2024
  • (2024)Range Cache: An Efficient Cache Component for Accelerating Range Queries on LSM - Based Key-Value Stores2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00044(488-500)Online publication date: 13-May-2024
  • (2023)Improving LSM-Tree Based Key-Value Stores With Fine-Grained Compaction MechanismIEEE Transactions on Cloud Computing10.1109/TCC.2023.332964611:4(3778-3796)Online publication date: Oct-2023
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cover image ACM Conferences
SIGMOD '19: Proceedings of the 2019 International Conference on Management of Data
June 2019
2106 pages
ISBN:9781450356435
DOI:10.1145/3299869
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 June 2019

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Author Tags

  1. adaptive
  2. b-tree
  3. data structures
  4. key-value
  5. lsm-tree
  6. nosql

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  • Extended-abstract

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SIGMOD/PODS '19
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SIGMOD/PODS '19: International Conference on Management of Data
June 30 - July 5, 2019
Amsterdam, Netherlands

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SIGMOD '19 Paper Acceptance Rate 88 of 430 submissions, 20%;
Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

View all
  • (2024)BushStore: Efficient B+Tree Group Indexing for LSM-Tree in Non-Volatile Memory2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00316(4127-4139)Online publication date: 13-May-2024
  • (2024)Range Cache: An Efficient Cache Component for Accelerating Range Queries on LSM - Based Key-Value Stores2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00044(488-500)Online publication date: 13-May-2024
  • (2023)Improving LSM-Tree Based Key-Value Stores With Fine-Grained Compaction MechanismIEEE Transactions on Cloud Computing10.1109/TCC.2023.332964611:4(3778-3796)Online publication date: Oct-2023
  • (2023)Morphtree: a polymorphic main-memory learned index for dynamic workloadsThe VLDB Journal10.1007/s00778-023-00823-y33:4(1065-1084)Online publication date: 1-Dec-2023
  • (2022)CloudJumpProceedings of the VLDB Endowment10.14778/3554821.355483415:12(3432-3444)Online publication date: 29-Sep-2022
  • (2022)CosineProceedings of the VLDB Endowment10.14778/3485450.348546115:1(112-126)Online publication date: 14-Jan-2022
  • (2022)Efficient R-Tree Exploration for Big Spatial DataAdvanced Intelligent Systems for Sustainable Development (AI2SD’2020)10.1007/978-3-030-90639-9_70(865-874)Online publication date: 10-Feb-2022
  • (2021)Towards a Benchmark for Learned Systems2021 IEEE 37th International Conference on Data Engineering Workshops (ICDEW)10.1109/ICDEW53142.2021.00029(127-133)Online publication date: Apr-2021

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