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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
5.1121061e-05
Overall Rank
9,814 | 34.22%
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
10,561 NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling: [Experiments & Analysis] 2026 SIGMOD 4.9605343e-05
10,566 On Self-Designing Learned Indexes 2026 SIGMOD 4.9605343e-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 0.00046249672
427 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00018429918
461 The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds 2020 VLDB 0.00017835351
774 FITing-Tree: A Data-aware Index Structure 2019 SIGMOD 0.00014063511
834 Benchmarking Learned Indexes 2021 VLDB 0.00013539098
906 HOT: A Height Optimized Trie Index for Main-Memory Database Systems 2018 SIGMOD 0.00013129817
964 Reducing the Storage Overhead of Main-Memory OLTP Databases with Hybrid Indexes 2016 SIGMOD 0.00012798312
1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012181459
1,529 Updatable Learned Index with Precise Positions 2021 VLDB 0.00010320909
1,538 On Multi-Column Foreign Key Discovery 2010 VLDB 0.00010295575
2,254 FINEdex: A Fine-grained Learned Index Scheme for Scalable and Concurrent Memory Systems 2022 VLDB 8.7429699e-05
2,590 Are Updatable Learned Indexes Ready? 2022 VLDB 8.2368464e-05
3,207 CDFShop: Exploring and Optimizing Learned Index Structures 2020 SIGMOD 7.5187675e-05
3,249 TreeLine: An Update-In-Place Key-Value Store for Modern Storage 2023 VLDB 7.4761584e-05
3,632 Learned Index: A Comprehensive Experimental Evaluation 2023 VLDB 7.1274345e-05
4,385 NFL: Robust Learned Index via Distribution Transformation 2022 VLDB 6.613814e-05
4,389 DILI: A Distribution-Driven Learned Index 2023 VLDB 6.6111249e-05
4,621 The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures 2022 SIGMOD 6.4828493e-05
4,656 PLIN: A Persistent Learned Index for Non-Volatile Memory with High Performance and Instant Recovery 2023 VLDB 6.468994e-05
4,727 Hist-Tree: Those Who Ignore It Are Doomed to Learn 2021 CIDR 6.4327925e-05
5,421 FILM: a Fully Learned Index for Larger-than-Memory Databases 2023 VLDB 6.1231965e-05
5,728 Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data 2023 SIGMOD 5.9979958e-05
5,854 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 5.9520525e-05
6,109 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 5.8676956e-05
6,279 A Critical Analysis of Recursive Model Indexes 2022 VLDB 5.8090653e-05
6,622 Making In-Memory Learned Indexes Efficient on Disk 2024 SIGMOD 5.7136886e-05
6,802 SALI: A Scalable Adaptive Learned Index Framework based on Probability Models 2023 SIGMOD 5.6623052e-05
7,314 Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction 2024 SIGMOD 5.5425359e-05
8,091 Two is Better Than One: The Case for 2-Tree for Skewed Data Sets 2023 CIDR 5.3744333e-05
8,223 Algorithmic Complexity Attacks on Dynamic Learned Indexes 2024 VLDB 5.3584214e-05
8,825 PACE: Poisoning Attacks on Learned Cardinality Estimation 2024 SIGMOD 5.2543246e-05
9,181 Towards Systematic Index Dynamization 2024 VLDB 5.1989155e-05
9,627 Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs 2024 SIGMOD 5.1369088e-05
9,707 Robustness of Updatable Learning-based Index Advisors against Poisoning Attack 2024 SIGMOD 5.1254261e-05
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