Grafite: Taming Adversarial Queries with Optimal Range Filters
Summary: Grafite provides a range filter with optimal adversarial guarantees: with B bits per key, query time O(1) and FPR ≤ l/2^(B-2). It outperforms existing range filters across datasets, workloads, and correlated queries, and also introduces a simple heuristic whose uncorrelated performance approaches the best. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Marco Costa (University of Pisa)
- 2. Paolo Ferragina (University of Pisa)
- 3. Giorgio Vinciguerra (University of Pisa)
BibTeX Citation
@inproceedings{costa_sigmod24,
title = {{Grafite: Taming Adversarial Queries with Optimal Range Filters}},
author = {Costa, Marco and Ferragina, Paolo and Vinciguerra, Giorgio},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3639258},
url = {https://dl.acm.org/doi/10.1145/3639258},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 880 | SuRF: Practical Range Query Filtering with Fast Succinct Tries | 2018 | SIGMOD | 0.00013432693 |
| 1,126 | Adaptive Range Filters for Cold Data: Avoiding Trips to Siberia | 2013 | VLDB | 0.00012078607 |
| 1,213 | MyRocks: LSM-Tree Database Storage Engine Serving Facebook's Social Graph | 2020 | VLDB | 0.00011646797 |
| 2,698 | Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores | 2020 | SIGMOD | 8.2450522e-05 |
| 2,919 | SNARF: A Learning-Enhanced Range Filter | 2022 | VLDB | 7.9628657e-05 |
| 4,119 | Proteus: A Self-Designing Range Filter | 2022 | SIGMOD | 6.8907395e-05 |
| 4,516 | The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures | 2022 | SIGMOD | 6.6489359e-05 |
| 4,960 | InfiniFilter: Expanding Filters to Infinity and Beyond | 2023 | SIGMOD | 6.4280133e-05 |
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|---|---|---|---|---|
| 1 | 8,308 | Diva: Dynamic Range Filter for Var-Length Keys and Queries | 2025 | VLDB |
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