A Critical Analysis of Recursive Model Indexes
Summary: Broad, inventor-independent analysis of Recursive Model Indexes reveals that hyperparameters beyond model type and layer size--notably error bounds and search strategies--impact performance. A simple configuration guideline delivers competitive RMIs and learned indexes without costly enumeration, with 2.5x--6.3x build-time speedups. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Marcel Maltry (Saarland University)
- 2. Jens Dittrich (Saarland University)
BibTeX Citation
@article{maltry_vldb22,
title = {{A Critical Analysis of Recursive Model Indexes}},
author = {Maltry, Marcel and Dittrich, Jens},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {5},
pages = {1079--1091},
doi = {10.14778/3510397.3510405},
url = {https://doi.org/10.14778/3510397.3510405},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,806 | Are Updatable Learned Indexes Ready? | 2022 | VLDB | 8.1013097e-05 |
| 3,792 | Learned Index: A Comprehensive Experimental Evaluation | 2023 | VLDB | 7.1220982e-05 |
| 5,974 | Towards instance-optimized data systems | 2021 | VLDB | 6.0230488e-05 |
| 6,874 | SALI: A Scalable Adaptive Learned Index Framework based on Probability Models | 2023 | SIGMOD | 5.7489487e-05 |
| 8,234 | The Case for Learned In-Memory Joins | 2023 | VLDB | 5.460955e-05 |
| 9,411 | Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs | 2024 | SIGMOD | 5.274743e-05 |
| 9,599 | Understanding Robustness Issues of Updatable Learned Indexes: [Experiments & Analysis] | 2026 | SIGMOD | 5.2492748e-05 |
| 10,682 | VEGA: An Active-tuning Learned Index with Group-Wise Learning Granularity | 2025 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 43 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00046060254 |
| 86 | Automatic Database Management System Tuning Through Large-scale Machine Learning | 2017 | SIGMOD | 0.00035316107 |
| 234 | Self-Driving Database Management Systems | 2017 | CIDR | 0.00023810722 |
| 278 | FAST: Fast Architecture Sensitive Tree Search on Modern CPUs and GPUs | 2010 | SIGMOD | 0.00022476841 |
| 323 | DeepDB: Learn from Data, not from Queries! | 2020 | VLDB | 0.00021264788 |
| 447 | ALEX: An Updatable Adaptive Learned Index | 2020 | SIGMOD | 0.00018322593 |
| 477 | The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds | 2020 | VLDB | 0.00017851226 |
| 790 | FITing-Tree: A Data-aware Index Structure | 2019 | SIGMOD | 0.0001401445 |
| 847 | Benchmarking Learned Indexes | 2021 | VLDB | 0.0001365768 |
| 3,152 | CDFShop: Exploring and Optimizing Learned Index Structures | 2020 | SIGMOD | 7.7003613e-05 |
| 4,660 | Hist-Tree: Those Who Ignore It Are Doomed to Learn | 2021 | CIDR | 6.5797541e-05 |
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| 1 | 4,660 | Hist-Tree: Those Who Ignore It Are Doomed to Learn | 2021 | CIDR |
| 2 | 10,984 | Benchmarking Adaptive Multidimensional Indices | 2025 | VLDB |
| 3 | 4,643 | Learned Index Benefits: Machine Learning Based Index Performance Estimation | 2022 | VLDB |
| 4 | 7,392 | Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction | 2024 | SIGMOD |
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| 6 | 4,516 | The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures | 2022 | SIGMOD |
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| 9 | 847 | Benchmarking Learned Indexes | 2021 | VLDB |
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