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Proteus: A Self-Designing Range Filter

Summary: Self-designing approximate range filter Proteus tunes itself from samples to minimize FPR under a fixed space. CPFPR unifies probabilistic and deterministic design spaces; in RocksDB it yields up to 5.3x end-to-end gains over SuRF/Rosetta with low modeling cost and robust workloads. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6539
Venue
SIGMOD
Year
2022
Pagerank
6.8907395e-05
Overall Rank
4,119 | 71.75%
DOI
10.1145/3514221.3526167

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{knorr_sigmod22,
        title = {{Proteus: A Self-Designing Range Filter}},
        author = {Knorr, Eric R. and Lemaire, Baptiste and Lim, Andrew and Luo, Siqiang and Zhang, Huanchen and Idreos, Stratos and Mitzenmacher, Michael},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3526167},
        url = {https://dl.acm.org/doi/10.1145/3514221.3526167},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 22 of 22 citing papers.

Rank Citing Paper Year Venue Pagerank
4,664 GRF: A Global Range Filter for LSM-Trees with Shape Encoding 2024 SIGMOD 6.5787544e-05
4,841 Grafite: Taming Adversarial Queries with Optimal Range Filters 2024 SIGMOD 6.4831558e-05
4,960 InfiniFilter: Expanding Filters to Infinity and Beyond 2023 SIGMOD 6.4280133e-05
5,261 Oasis: An Optimal Disjoint Segmented Learned Range Filter 2024 VLDB 6.2955539e-05
6,416 Memento Filter: A Fast, Dynamic, and Robust Range Filter 2024 SIGMOD 5.8829474e-05
6,843 Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads 2023 SIGMOD 5.7573899e-05
7,757 CAMAL: Optimizing LSM-trees via Active Learning 2024 SIGMOD 5.5508469e-05
7,776 Aleph Filter: To Infinity in Constant Time 2024 VLDB 5.5464036e-05
7,846 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.5331459e-05
8,156 How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice 2025 SIGMOD 5.4765648e-05
8,308 Diva: Dynamic Range Filter for Var-Length Keys and Queries 2025 VLDB 5.4562543e-05
8,811 ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads 2026 VLDB 5.3652966e-05
9,021 Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space 2024 SIGMOD 5.3305499e-05
9,457 Rethinking The Compaction Policies in LSM-trees 2025 SIGMOD 5.2642945e-05
9,463 Hourglass: An Adaptive Range Filter with Lightweight Hybrid Encoding 2026 SIGMOD 5.2634238e-05
9,465 Are Joins over LSM-trees Ready? Take RocksDB as an Example 2025 VLDB 5.2634238e-05
9,535 Disco: A Compact Index for LSM-trees 2025 SIGMOD 5.2533796e-05
10,134 A Multi-tenant Relational OLTP Database at Salesforce 2026 CIDR 5.093636e-05
10,426 Aeris Filter: A Strongly and Monotonically Adaptive Range Filter 2026 SIGMOD 5.093636e-05
10,465 Improving Range Scan Performance in LSM-trees with Group Caching 2026 SIGMOD 5.093636e-05
11,281 LavaStore: ByteDance's Purpose-built, High-performance, Cost-effective Local Storage Engine for Cloud Services 2024 VLDB 5.093636e-05
11,423 A Learned Cuckoo Filter for Approximate Membership Queries over Variable-sized Sliding Windows on Data Streams 2023 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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