UDFBench: A Tool for Benchmarking UDF Queries on SQL Engines
Summary: UDFBench focuses on UDF-centric query processing, profiling overheads and optimization opportunities for scalar, aggregate, and table UDFs. Modular benchmark with 42 UDFs, 21 queries, real data, across MonetDB, PostgreSQL, DuckDB, SQLite; Python/Jupyter API enables reproducible experiments. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yannis Foufoulas (Athena - Research and Innovation Center in Information, Communication and Knowledge Technologies)
- 2. Theoni Palaiologou (Athena - Research and Innovation Center in Information, Communication and Knowledge Technologies; National and Kapodistrian University of Athens)
- 3. Alkis Simitsis (Athena - Research and Innovation Center in Information, Communication and Knowledge Technologies)
BibTeX Citation
@inproceedings{foufoulas_sigmod25,
title = {{UDFBench: A Tool for Benchmarking UDF Queries on SQL Engines}},
author = {Foufoulas, Yannis and Palaiologou, Theoni and Simitsis, Alkis},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3725139},
url = {https://dl.acm.org/doi/10.1145/3722212.3725139},
year = {2025}
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 18 | How Good Are Query Optimizers, Really? | 2016 | VLDB | 0.00059284255 |
| 1,768 | Tuplex: Data Science in Python at Native Code Speed | 2021 | SIGMOD | 9.8041636e-05 |
| 1,892 | Procedural Extensions of SQL: Understanding their usage in the wild | 2021 | VLDB | 9.5277793e-05 |
| 2,094 | Tupleware: "Big" Data, Big Analytics, Small Clusters | 2015 | CIDR | 9.1819738e-05 |
| 6,314 | YeSQL: "You extend SQL" with Rich and Highly Performant User-Defined Functions in Relational Databases | 2022 | VLDB | 5.9157364e-05 |
| 8,096 | Efficient Execution of User-Defined Functions in SQL Queries | 2023 | VLDB | 5.4875738e-05 |
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