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Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction

Summary: Hyper: hybrid learned index construction to break the usual performance/memory trade-off in dynamic settings. Bottom-up leaves + top-down internals yield concurrent write support and strong speedups with drastically lower memory than prior learned indexes. (summarized by gpt-5.4-mini on May 24 2026)

Paper ID
h4b305f11385d3d8e
Venue
SIGMOD
Year
2024
Pagerank
5.5425359e-05
Overall Rank
7,314 | 50.98%
DOI
10.1145/3654948

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhang_sigmod24,
        title = {{Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction}},
        author = {Zhang, Shunkang and Qi, Ji and Yao, Xin and Brinkmann, André},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3654948},
        url = {https://dl.acm.org/doi/10.1145/3654948},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 19 of 19 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
61 Integrating Compression and Execution in Column-Oriented Database Systems 2006 SIGMOD 0.00039323387
280 FAST: Fast Architecture Sensitive Tree Search on Modern CPUs and GPUs 2010 SIGMOD 0.00022267903
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
515 Tree Indexing on Solid State Drives 2010 VLDB 0.00016989841
774 FITing-Tree: A Data-aware Index Structure 2019 SIGMOD 0.00014063511
906 HOT: A Height Optimized Trie Index for Main-Memory Database Systems 2018 SIGMOD 0.00013129817
1,190 Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads 2021 VLDB 0.00011564169
1,529 Updatable Learned Index with Precise Positions 2021 VLDB 0.00010320909
2,247 Efficiently Searching In-Memory Sorted Arrays: Revenge of the Interpolation Search? 2019 SIGMOD 8.7591557e-05
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
3,632 Learned Index: A Comprehensive Experimental Evaluation 2023 VLDB 7.1274345e-05
4,389 DILI: A Distribution-Driven Learned Index 2023 VLDB 6.6111249e-05
5,398 Order-Preserving Key Compression for In-Memory Search Trees 2020 SIGMOD 6.1338952e-05
6,802 SALI: A Scalable Adaptive Learned Index Framework based on Probability Models 2023 SIGMOD 5.6623052e-05
8,195 Hyperion: Building the Largest In-memory Search Tree 2019 SIGMOD 5.3639085e-05
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