Survivorship Bias in Industrial Database Workloads

Summary: Industrial workload traces reflect a negotiation: users adapt queries to exploit platform strengths and avoid weak features, so traces are biased toward "surviving" patterns. This survivorship bias undermines assuming traces fully represent user needs and calls for contextualized workload collection, analysis, and benchmark design. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 583
Venue: CIDR
Year: 2026
Pagerank: 4.1945683e-05
Overall Rank: 9,981 | 30.57%
DOI: -

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Rank	Citing Paper	Year	Venue	Pagerank

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Showing 18 of 18 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
659	The Making of TPC-DS	2006	VLDB	0.00018500853
1,284	Amazon Redshift Re-invented	2022	SIGMOD	0.00012837822
1,943	Procella: Unifying serving and analytical data at YouTube	2019	VLDB	0.00010012569
2,106	Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing	2025	CIDR	9.5342543e-05
3,178	Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet	2024	VLDB	7.4325992e-05
4,690	Deploying a Steered Query Optimizer in Production at Microsoft	2022	SIGMOD	5.997226e-05
4,717	Cloud Analytics Benchmark	2023	VLDB	5.9751539e-05
5,531	Presto: A Decade of SQL Analytics at Meta	2023	SIGMOD	5.4549499e-05
5,640	AutoSteer: Learned Query Optimization for Any SQL Database	2023	VLDB	5.3933314e-05
5,832	Stage: Query Execution Time Prediction in Amazon Redshift	2024	SIGMOD	5.3111109e-05
6,685	How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks	2025	SIGMOD	4.9627485e-05
6,972	Predicate Caching: Query-Driven Secondary Indexing for Cloud Data Warehouses	2024	SIGMOD	4.8785237e-05
8,020	The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions	2024	VLDB	4.6040862e-05
8,131	Sibyl: Forecasting Time-Evolving Query Workloads	2024	SIGMOD	4.5784634e-05
8,659	Learned Offline Query Planning via Bayesian Optimization	2025	SIGMOD	4.4722928e-05
9,391	Database as Runtime: Compiling LLMs to SQL for In-database Model Serving	2025	SIGMOD	4.3441378e-05
9,392	Demonstrating SQLBarber: Leveraging Large Language Models to Generate Customized and Realistic SQL Workloads	2025	SIGMOD	4.3441378e-05
9,587	Low Rank Learning for Offline Query Optimization	2025	SIGMOD	4.3215645e-05

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