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Benchmarking Learned Indexes

arXiv 2006.12804 ↗First posted 23 Jun 2020cs.DBcited by 27

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Abstract (arXiv)

Recent advancements in learned index structures propose replacing existing index structures, like B-Trees, with approximate learned models. In this work, we present a unified benchmark that compares well-tuned implementations of three learned index structures against several state-of-the-art "traditional" baselines. Using four real-world datasets, we demonstrate that learned index structures can indeed outperform non-learned indexes in read-only in-memory workloads over a dense array. We also investigate the impact of caching, pipelining, dataset size, and key size. We study the performance profile of learned index structures, and build an explanation for why learned models achieve such good performance. Finally, we investigate other important properties of learned index structures, such as their performance in multi-threaded systems and their build times.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jun 2020.

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Citing papers per year: 2021: 7; 2022: 7; 2023: 6; 2024: 2; 2025: 2; 2026: 3.

27 papers.

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  1. 2021Federated Learning on Non-IID Data Silos: An Experimental Studycited by 566
  2. 2023Data-centric Artificial Intelligence: A Surveycited by 202
  3. 2021CARMI: A Cache-Aware Learned Index with a Cost-based Construction Algorithmcited by 8
  4. 2021Bounding the Last Mile: Efficient Learned String Indexingcited by 6
  5. 2023WISK: A Workload-aware Learned Index for Spatial Keyword Queriescited by 6
  6. 2023On Distribution Dependent Sub-Logarithmic Query Time of Learned Indexingcited by 6
  7. 2021Learned Sorted Table Search and Static Indexes in Small Model Spacecited by 4
  8. 2021On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filterscited by 4
  9. 2024A Survey of Learned Indexes for the Multi-dimensional Spacecited by 4
  10. 2024Accelerating String-Key Learned Index Structures via Memoization-based Incremental Trainingcited by 4
  11. 2021Towards Practical Learned Indexingcited by 3
  12. 2022On the Suitability of Neural Networks as Building Blocks for The Design of Efficient Learned Indexescited by 3
15 more
  1. 2021Micro-architectural Analysis of a Learned Indexcited by 2
  2. 2022Standard Vs Uniform Binary Search and Their Variants in Learned Static Indexing: The Case of the Searching on Sorted Data Benchmarking Software Platformcited by 2
  3. 2022Proteus: A Self-Designing Range Filtercited by 2
  4. 2022LSI: A Learned Secondary Index Structurecited by 1
  5. 2025DobLIX: A Dual-Objective Learned Index for Log-Structured Merge Treescited by 1
  6. 2026Mathematical Foundations of Poisoning Attacks on Linear Regression over Cumulative Distribution Functionscited by 1
  7. 2022Multi-agent Databases via Independent Learningcited by 0
  8. 2022Learned k-NN Distance Estimationcited by 0
  9. 2022A Critical Analysis of Classifier Selection in Learned Bloom Filterscited by 0
  10. 2023Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guaranteescited by 0
  11. 2023LearnedSort as a learning-augmented SampleSort: Analysis and Parallelizationcited by 0
  12. 2023From Specific to Generic Learned Sorted Set Dictionaries: A Theoretically Sound Paradigm Yelding Competitive Data Structural Boosters in Practicecited by 0
  13. 2025Piecewise Linear Approximation in Learned Index Structures: Theoretical and Empirical Analysiscited by 0
  14. 2026Lower Bounds for the Algorithmic Complexity of Learned Indexescited by 0
  15. 2026Adversarial Query Synthesis via Bayesian Optimizationcited by 0