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BIPie: Fast Selection and Aggregation on Encoded Data using Operator Specialization

Summary: BIPie: fast selection and aggregation on encoded data via operator specialization, fusing decoding, filtering, and GROUP BY on MemSQL. Leverages SIMD and modern CPUs; 2–4× speedups vs TPC-H Q1, highlights decode/select/aggregate interdependence. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5491
Venue
SIGMOD
Year
2018
Pagerank
4.306318e-05
Overall Rank
9,671 | 32.73%
DOI
10.1145/3183713.3190658

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
3,680 SingleStore-V: An Integrated Vector Database System in SingleStore 2024 VLDB 6.8496415e-05
5,678 Cloud-Native Transactions and Analytics in SingleStore 2022 SIGMOD 5.3746593e-05
6,221 Charting the Design Space of Query Execution using VOILA 2021 VLDB 5.1512158e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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