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Cheetah: Accelerating Database Queries with Switch Pruning

Summary: Offloads part of query processing to programmable switches via data pruning to drop entries guaranteed not to affect results. Cheetah implements pruning algorithms on Barefoot Tofino and Spark, delivering 40–200% faster query completion than Spark across diverse workloads. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5914
Venue
SIGMOD
Year
2020
Pagerank
5.1239052e-05
Overall Rank
6,280 | 56.36%
DOI
10.1145/3318464.3389698

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank Citing Paper Year Venue Pagerank
4,979 In-Network Support for Transaction Triaging 2021 VLDB 5.7830279e-05
8,075 P4DB - The Case for In-Network OLTP 2022 SIGMOD 4.5888845e-05
8,269 GraphINC: Graph Pattern Mining at Network Speed 2023 SIGMOD 4.5406632e-05
9,458 DPDPU: Data Processing with DPUs 2025 CIDR 4.3344018e-05
10,098 P4KVS: A Role-Replica Separation Offloading Method to Achieve In-Network Consistency for KV Stores Based on P4 Switches 2026 SIGMOD 4.1905499e-05
11,157 Templating Shuffles 2023 CIDR 4.1905499e-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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