How to Optimize SQL Queries? A Comparison Between Split, Holistic, and Hybrid Approaches

Summary: Contrasts split vs holistic query optimization across full QEP decisions (join orders, access methods, physical operator implementations), highlighting stark optimization-time vs plan-quality tradeoffs. Proposes a top-k hybrid that recovers holistic optima with optimization time near split, validated experimentally in the mutable research DB. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: hd7e892fc4c5147cd
Venue: VLDB
Year: 2025
Pagerank: 5.0742707e-05
Overall Rank: 10,140 | 31.83%
DOI: 10.14778/3749646.3749663

Incoming Non-self Citations Over Time

Authors

1. Luca Gretscher (Saarland University)
2. Jens Dittrich (Saarland University)

BibTeX Citation

@article{gretscher_vldb25,
        title = {{How to Optimize SQL Queries? A Comparison Between Split, Holistic, and Hybrid Approaches}},
        author = {Gretscher, Luca and Dittrich, Jens},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {11},
        pages = {3910--3922},
        doi = {10.14778/3749646.3749663},
        url = {https://doi.org/10.14778/3749646.3749663},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,741	OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning	2026	VLDB	4.9793485e-05
10,832	ReSequel: Robust LLM-assisted Query Rewriting and Optimization using Templatization and Sampling	2026	VLDB	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 17 of 17 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	Access Path Selection in a Relational Database Management System	1979	SIGMOD	0.0023947656
15	How Good Are Query Optimizers, Really?	2016	VLDB	0.00061066921
21	Efficiently Compiling Efficient Query Plans for Modern Hardware	2011	VLDB	0.00056855599
145	Neo: A Learned Query Optimizer	2019	VLDB	0.0002908188
321	Measuring the Complexity of Join Enumeration in Query Optimization	1990	VLDB	0.00021088704
402	Worst-case Optimal Join Algorithms	2012	PODS	0.00019104625
724	Fundamental Techniques for Order Optimization	1996	SIGMOD	0.00014477566
796	Rapid Bushy Join-order Optimization with Cartesian Products	1996	SIGMOD	0.00013938011
1,301	Analysis of Two Existing and One New Dynamic Programming Algorithm for the Generation of Optimal Bushy Join Trees without Cross Products	2006	VLDB	0.00011112842
1,726	Optimal Top-Down Join Enumeration	2007	SIGMOD	9.788916e-05
1,734	Flow-Loss: Learning Cardinality Estimates That Matter	2021	VLDB	9.7545773e-05
3,595	A Combined Framework for Grouping and Order Optimization	2004	VLDB	7.1803562e-05
4,209	Accelerating Queries with Group-By and Join by Groupjoin	2011	VLDB	6.7339503e-05
4,401	Avoiding Sorting and Grouping In Processing Queries	2003	VLDB	6.6148785e-05
8,039	Efficiently Computing Join Orders with Heuristic Search	2023	SIGMOD	5.4017809e-05
9,784	Memory Efficient Scheduling of Query Pipeline Execution	2022	CIDR	5.1285917e-05
11,672	mutable: A Modern DBMS for Research and Fast Prototyping	2023	CIDR	4.9793485e-05

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