Saving Money for Analytical Workloads in the Cloud
Summary: Exploit differences in cloud billing (compute-time vs bytes-scanned) by classifying analytical queries as compute- or IO-bound and selecting execution modalities that minimize monetary cost while meeting user runtime constraints. Implement cost-aware plan generation that mixes pricing models (and clouds), yielding up to 56% workload and 90% per-query savings and robust gains across vendor price variations. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,856 | CloudGlide: Deconstructing the Landscape of Cloud-Based Analytics | 2025 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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