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Workload Optimization using SharedDB

Summary: SharedDB executes SQL operators in batches with cross-query sharing across all running queries, instead of one-at-a-time. It enables sharing without requiring common subexpressions, reducing inter-query interference and handling diverse workloads with higher throughput. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4612
Venue
SIGMOD
Year
2013
Pagerank
4.6935227e-05
Overall Rank
7,622 | 46.98%
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
3,429 Real-time Workload Pattern Analysis for Large-scale Cloud Databases 2023 VLDB 7.1010535e-05
6,624 Fast-Forwarding to Desired Visualizations with zenvisage 2017 CIDR 4.9890732e-05
8,075 AJoin: Ad-hoc Stream Joins at Scale 2020 VLDB 4.5917655e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
940 SharedDB: Killing One Thousand Queries With One Stone 2012 VLDB 0.00015173166
2,372 Predictable Performance for Unpredictable Workloads 2009 VLDB 8.947963e-05
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