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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
h38d1d59eb1a75b3a
Venue
SIGMOD
Year
2026
Pagerank
5.1314952e-05
Overall Rank
9,777 | 34.27%
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
10,484 NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling: [Experiments & Analysis] 2026 SIGMOD 4.9793485e-05
10,489 On Self-Designing Learned Indexes 2026 SIGMOD 4.9793485e-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
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046284649
430 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00018409112
463 The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds 2020 VLDB 0.00017804544
779 FITing-Tree: A Data-aware Index Structure 2019 SIGMOD 0.00014030069
848 Benchmarking Learned Indexes 2021 VLDB 0.00013506188
907 HOT: A Height Optimized Trie Index for Main-Memory Database Systems 2018 SIGMOD 0.00013158824
971 Reducing the Storage Overhead of Main-Memory OLTP Databases with Hybrid Indexes 2016 SIGMOD 0.00012766019
1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202282
1,532 On Multi-Column Foreign Key Discovery 2010 VLDB 0.00010332696
1,550 Updatable Learned Index with Precise Positions 2021 VLDB 0.00010282449
2,277 FINEdex: A Fine-grained Learned Index Scheme for Scalable and Concurrent Memory Systems 2022 VLDB 8.7075835e-05
2,636 Are Updatable Learned Indexes Ready? 2022 VLDB 8.1941043e-05
3,206 CDFShop: Exploring and Optimizing Learned Index Structures 2020 SIGMOD 7.5397402e-05
3,232 TreeLine: An Update-In-Place Key-Value Store for Modern Storage 2023 VLDB 7.50343e-05
3,697 Learned Index: A Comprehensive Experimental Evaluation 2023 VLDB 7.0882335e-05
4,375 DILI: A Distribution-Driven Learned Index 2023 VLDB 6.6292167e-05
4,508 NFL: Robust Learned Index via Distribution Transformation 2022 VLDB 6.5704964e-05
4,616 The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures 2022 SIGMOD 6.5000712e-05
4,641 PLIN: A Persistent Learned Index for Non-Volatile Memory with High Performance and Instant Recovery 2023 VLDB 6.4899953e-05
4,721 Hist-Tree: Those Who Ignore It Are Doomed to Learn 2021 CIDR 6.4541703e-05
5,571 FILM: a Fully Learned Index for Larger-than-Memory Databases 2023 VLDB 6.080267e-05
5,716 Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data 2023 SIGMOD 6.0194657e-05
5,865 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 5.9659203e-05
6,274 A Critical Analysis of Recursive Model Indexes 2022 VLDB 5.8271888e-05
6,308 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 5.8177833e-05
6,821 Making In-Memory Learned Indexes Efficient on Disk 2024 SIGMOD 5.6720444e-05
7,018 SALI: A Scalable Adaptive Learned Index Framework based on Probability Models 2023 SIGMOD 5.619958e-05
7,535 Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction 2024 SIGMOD 5.5003117e-05
8,129 Two is Better Than One: The Case for 2-Tree for Skewed Data Sets 2023 CIDR 5.3938156e-05
8,200 Algorithmic Complexity Attacks on Dynamic Learned Indexes 2024 VLDB 5.3787447e-05
8,800 PACE: Poisoning Attacks on Learned Cardinality Estimation 2024 SIGMOD 5.2742531e-05
9,149 Towards Systematic Index Dynamization 2024 VLDB 5.2186338e-05
9,593 Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs 2024 SIGMOD 5.156392e-05
9,671 Robustness of Updatable Learning-based Index Advisors against Poisoning Attack 2024 SIGMOD 5.1448657e-05
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