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PIQL: A Performance Insightful Query Language

Summary: PIQL targets web-scale workloads by layering a declarative query language over distributed key-value stores. It expresses common website queries with guaranteed I/O bounds, delivering predictable performance and reducing the need for onerous explicit indexing and imperative lookups. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4351
Venue
SIGMOD
Year
2010
Pagerank
6.4319226e-05
Overall Rank
4,117 | 71.39%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
94 CrowdDB: Answering Queries with Crowdsourcing 2011 SIGMOD 0.00051273089
11,677 Block as a Value for SQL over NoSQL 2019 VLDB 4.1905499e-05
11,793 BEAS: Bounded Evaluation of SQL Queries 2017 SIGMOD 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,706 SCADS: Scale-Independent Storage for Social Computing Applications 2009 CIDR 0.00010806188
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