Hyperion: Building the Largest In-memory Search Tree
Summary: Hyperion, a trie-based in-memory key-value store, builds the largest in-memory search tree with extreme space efficiency via linear scans instead of vector-unit tricks. A custom allocator yields high density, delivering competitive point queries and exceptional range queries while shrinking the index footprint and achieving over 2x memory-to-performance on randomized strings. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Markus Mäsker (Johannes Gutenberg University Mainz)
- 2. Tim Süß (Fulda University of Applied Sciences)
- 3. Lars Nagel (Loughborough University)
- 4. Lingfang Zeng (Huazhong University of Science and Technology)
- 5. André Brinkmann (Johannes Gutenberg University Mainz)
BibTeX Citation
@inproceedings{masker_sigmod19,
title = {{Hyperion: Building the Largest In-memory Search Tree}},
author = {Mäsker, Markus and Süß, Tim and Nagel, Lars and Zeng, Lingfang and Brinkmann, André},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3319870},
url = {https://dl.acm.org/doi/10.1145/3299869.3319870},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,946 | Spruce: A Fast yet Space-saving Structure for Dynamic Graph Storage | 2024 | SIGMOD | 6.4319457e-05 |
| 5,285 | Order-Preserving Key Compression for In-Memory Search Trees | 2020 | SIGMOD | 6.2821588e-05 |
| 7,392 | Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction | 2024 | SIGMOD | 5.6265456e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 67 | Making B+-Trees Cache Conscious in Main Memory | 2000 | SIGMOD | 0.00038461275 |
| 204 | Cache Conscious Indexing for Decision-Support in Main Memory | 1999 | VLDB | 0.00025342994 |
| 278 | FAST: Fast Architecture Sensitive Tree Search on Modern CPUs and GPUs | 2010 | SIGMOD | 0.00022476841 |
| 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 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 5,285 | Order-Preserving Key Compression for In-Memory Search Trees | 2020 | SIGMOD |
| 2 | 5,954 | When Tree Meets Hash: Reducing Random Reads for Index Structures on Persistent Memories | 2023 | SIGMOD |
| 3 | 12,489 | Worst-Case Efficient Range Search Indexing | 2009 | PODS |
| 4 | 12,025 | Anti-Persistence on Persistent Storage: History-Independent Sparse Tables and Dictionaries | 2016 | PODS |
| 5 | 8,207 | The HV-tree: a Memory Hierarchy Aware Version Index | 2010 | VLDB |
| 6 | 9,635 | Memory-Efficient Search Trees for Database Management Systems | 2021 | SIGMOD |
| 7 | 882 | HOT: A Height Optimized Trie Index for Main-Memory Database Systems | 2018 | SIGMOD |
| 8 | 5,823 | HydraList: A Scalable In-Memory Index Using Asynchronous Updates and Partial Replication | 2020 | VLDB |
| 9 | 8,680 | The PH-Tree – A Space-Efficient Storage Structure and Multi-Dimensional Index | 2014 | SIGMOD |
| 10 | 7,392 | Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction | 2024 | SIGMOD |