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Understanding Robustness Issues of Updatable Learned Indexes: [Experiments & Analysis]

Summary: Systematic benchmarking shows updatable learned indexes lack robustness: real-time model instability erodes gains and they rarely beat traditional indexes in workloads. Root causes include overfitting and unbalanced structures; mitigations offered. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7535
Venue
SIGMOD
Year
2026
Pagerank
5.2492748e-05
Overall Rank
9,599 | 34.15%
DOI
10.1145/3749188

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{luo_sigmod26,
        title = {{Understanding Robustness Issues of Updatable Learned Indexes: [Experiments \& Analysis]}},
        author = {Luo, Yuanhui and Xie, Minhui and Tong, Yiheng and Jiang, Shichao and Chai, Yunpeng},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3749188},
        url = {https://dl.acm.org/doi/10.1145/3749188},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,272 NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling: [Experiments & Analysis] 2026 SIGMOD 5.093636e-05
10,277 On Self-Designing Learned Indexes 2026 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 34 of 34 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
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
882 HOT: A Height Optimized Trie Index for Main-Memory Database Systems 2018 SIGMOD 0.0001342403
964 Reducing the Storage Overhead of Main-Memory OLTP Databases with Hybrid Indexes 2016 SIGMOD 0.00012934147
1,061 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012369764
1,521 On Multi-Column Foreign Key Discovery 2010 VLDB 0.00010506299
1,551 Updatable Learned Index with Precise Positions 2021 VLDB 0.00010381398
2,233 FINEdex: A Fine-grained Learned Index Scheme for Scalable and Concurrent Memory Systems 2022 VLDB 8.8968964e-05
2,806 Are Updatable Learned Indexes Ready? 2022 VLDB 8.1013097e-05
3,152 CDFShop: Exploring and Optimizing Learned Index Structures 2020 SIGMOD 7.7003613e-05
3,535 TreeLine: An Update-In-Place Key-Value Store for Modern Storage 2023 VLDB 7.3333933e-05
3,792 Learned Index: A Comprehensive Experimental Evaluation 2023 VLDB 7.1220982e-05
4,300 DILI: A Distribution-Driven Learned Index 2023 VLDB 6.773869e-05
4,414 NFL: Robust Learned Index via Distribution Transformation 2022 VLDB 6.7159984e-05
4,516 The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures 2022 SIGMOD 6.6489359e-05
4,578 PLIN: A Persistent Learned Index for Non-Volatile Memory with High Performance and Instant Recovery 2023 VLDB 6.6210545e-05
4,660 Hist-Tree: Those Who Ignore It Are Doomed to Learn 2021 CIDR 6.5797541e-05
5,447 FILM: a Fully Learned Index for Larger-than-Memory Databases 2023 VLDB 6.2149491e-05
6,132 Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data 2023 SIGMOD 5.9660278e-05
6,163 A Critical Analysis of Recursive Model Indexes 2022 VLDB 5.9532723e-05
6,271 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 5.9326197e-05
6,323 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 5.9141228e-05
6,687 Making In-Memory Learned Indexes Efficient on Disk 2024 SIGMOD 5.8022308e-05
6,874 SALI: A Scalable Adaptive Learned Index Framework based on Probability Models 2023 SIGMOD 5.7489487e-05
7,392 Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction 2024 SIGMOD 5.6265456e-05
8,016 Two is Better Than One: The Case for 2-Tree for Skewed Data Sets 2023 CIDR 5.5070057e-05
8,039 Algorithmic Complexity Attacks on Dynamic Learned Indexes 2024 VLDB 5.5021992e-05
8,643 PACE: Poisoning Attacks on Learned Cardinality Estimation 2024 SIGMOD 5.3940849e-05
8,988 Towards Systematic Index Dynamization 2024 VLDB 5.3384135e-05
9,411 Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs 2024 SIGMOD 5.274743e-05
9,490 Robustness of Updatable Learning-based Index Advisors against Poisoning Attack 2024 SIGMOD 5.2629522e-05
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