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HIRE: A Hybrid Learned Index for Robust and Efficient Performance under Mixed Workloads
Summary: HIRE: hybrid learned in-memory index targeting robust mixed-workload performance, combining adaptive leaf nodes, model-accelerated internal nodes, and non-blocking recalibration to retain stability under updates. Aims to fix learned-index pain points—tail latency, range queries, and workload sensitivity—while outperforming classic indexes on throughput.
(summarized by gpt-5-mini on Apr 11 2026)
- Paper ID
- 7483
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 4.1945683e-05
- Overall Rank
- 10,172 | 29.24%
- DOI
-
10.1145/3786657
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Incoming Citations (Sorted by Pagerank)
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| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 102 |
The Case for Learned Index Structures |
2018 |
SIGMOD |
0.00049545203 |
| 826 |
ALEX: An Updatable Adaptive Learned Index |
2020 |
SIGMOD |
0.00016224841 |
| 857 |
The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds |
2020 |
VLDB |
0.00015882892 |
| 1,375 |
FITing-Tree: A Data-aware Index Structure |
2019 |
SIGMOD |
0.00012303141 |
| 1,460 |
Benchmarking Learned Indexes |
2021 |
VLDB |
0.00011887068 |
| 2,552 |
Updatable Learned Index with Precise Positions |
2021 |
VLDB |
8.5530411e-05 |
| 3,131 |
FINEdex: A Fine-grained Learned Index Scheme for Scalable and Concurrent Memory Systems |
2022 |
VLDB |
7.4985793e-05 |
| 4,084 |
APEX: A High-Performance Learned Index on Persistent Memory |
2022 |
VLDB |
6.4622113e-05 |
| 4,128 |
Are Updatable Learned Indexes Ready? |
2022 |
VLDB |
6.4292373e-05 |
| 4,646 |
CARMI: A Cache-Aware Learned Index with a Cost-based Construction Algorithm |
2022 |
VLDB |
6.0250374e-05 |
| 5,074 |
Learned Index: A Comprehensive Experimental Evaluation |
2023 |
VLDB |
5.7175726e-05 |
| 5,319 |
DILI: A Distribution-Driven Learned Index |
2023 |
VLDB |
5.5713974e-05 |
| 6,972 |
Predicate Caching: Query-Driven Secondary Indexing for Cloud Data Warehouses |
2024 |
SIGMOD |
4.8785237e-05 |
| 7,390 |
Making In-Memory Learned Indexes Efficient on Disk |
2024 |
SIGMOD |
4.7431654e-05 |
| 7,869 |
SALI: A Scalable Adaptive Learned Index Framework based on Probability Models |
2023 |
SIGMOD |
4.6315248e-05 |
| 7,894 |
LITS: An Optimized Learned Index for Strings |
2024 |
VLDB |
4.6240341e-05 |
| 8,101 |
Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction |
2024 |
SIGMOD |
4.5854141e-05 |
| 8,627 |
Limousine: Blending Learned and Classical Indexes to Self-Design Larger-than-Memory Cloud Storage Engines |
2024 |
SIGMOD |
4.4829101e-05 |
| 8,811 |
Tuning Hierarchical Learned Indexes on Disk and Beyond |
2022 |
SIGMOD |
4.4441574e-05 |
| 9,095 |
AirIndex: Versatile Index Tuning Through Data and Storage |
2023 |
SIGMOD |
4.3975034e-05 |
| 9,346 |
Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs |
2024 |
SIGMOD |
4.3532026e-05 |
| 9,618 |
A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach |
2025 |
SIGMOD |
4.3173366e-05 |
| 9,746 |
Why Are Learned Indexes So Effective but Sometimes Ineffective? |
2025 |
VLDB |
4.2897489e-05 |
| 10,949 |
SWIX: A Memory-efficient Sliding Window Learned Index |
2024 |
SIGMOD |
4.1945683e-05 |
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