An In-Depth Benchmarking of Text-to-SQL Systems
Summary: Rigorous, multi-class Text-to-SQL benchmark covering diverse query types beyond existing datasets. Systematic evaluation of several T2SQL systems with execution time and resource usage, revealing gaps, capabilities, and open challenges in current approaches. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Orest Gkini (Athena Research Center)
- 2. Theofilos Belmpas (Athena Research Center)
- 3. Georgia Koutrika (Athena Research Center)
- 4. Yannis Ioannidis (Athena Research Center; University of Athens)
BibTeX Citation
@inproceedings{gkini_sigmod21,
title = {{An In-Depth Benchmarking of Text-to-SQL Systems}},
author = {Gkini, Orest and Belmpas, Theofilos and Koutrika, Georgia and Ioannidis, Yannis},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3452836},
url = {https://dl.acm.org/doi/10.1145/3448016.3452836},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,852 | The Dawn of Natural Language to SQL: Are We Fully Ready? | 2024 | VLDB | 8.0455088e-05 |
| 3,339 | A Deep Dive into Deep Learning Approaches for Text-to-SQL Systems | 2021 | SIGMOD | 7.5047676e-05 |
| 8,945 | Generation of Training Examples for Tabular Natural Language Inference | 2023 | SIGMOD | 5.3480421e-05 |
| 9,136 | Sphinteract: Resolving Ambiguities in NL2SQL Through User Interaction | 2025 | VLDB | 5.3166292e-05 |
| 9,305 | The Power of Constraints in Natural Language to SQL Translation | 2025 | VLDB | 5.289545e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 37 | DISCOVER: Keyword Search in Relational Databases | 2002 | VLDB | 0.00048017193 |
| 179 | Constructing an Interactive Natural Language Interface for Relational Databases | 2015 | VLDB | 0.00026838277 |
| 212 | Efficient IR-Style Keyword Search over Relational Databases | 2003 | VLDB | 0.000247733 |
| 272 | BLINKS: Ranked Keyword Searches on Graphs | 2007 | SIGMOD | 0.00022695855 |
| 459 | ATHENA: An Ontology-Driven System for Natural Language Querying over Relational Data Stores | 2016 | VLDB | 0.00018101318 |
| 930 | SPARK: Top-k Keyword Query in Relational Databases | 2007 | SIGMOD | 0.0001312728 |
| 1,182 | SQAK: Doing More with Keywords | 2008 | SIGMOD | 0.00011778765 |
| 1,214 | SODA: Generating SQL for Business Users | 2012 | VLDB | 0.0001163751 |
| 5,130 | Natural Language Data Management and Interfaces: Recent Development and Open Challenges | 2017 | SIGMOD | 6.354484e-05 |
| 6,567 | MeanKS: Meaningful Keyword Search in Relational Databases with Complex Schema | 2014 | SIGMOD | 5.8380657e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,732 | RTS+: Reliable Text to SQL | 2025 | SIGMOD |
| 2 | 45 | Benchmarking Database Systems: A Systematic Approach | 1983 | VLDB |
| 3 | 10,406 | Test Data Generation for Complex SQL Queries | 2026 | SIGMOD |
| 4 | 10,537 | TACO: A Benchmark for Open-Domain Text-to-SQL with Ambiguous and Cross-Database Queries | 2026 | VLDB |
| 5 | 3,339 | A Deep Dive into Deep Learning Approaches for Text-to-SQL Systems | 2021 | SIGMOD |
| 6 | 10,510 | NL2SQLBench: A Modular Benchmarking Framework for LLM-Enabled NL2SQL Solutions | 2026 | VLDB |
| 7 | 7,071 | The TEXTURE Benchmark: Measuring Performance of Text Queries on a Relational DBMS | 2005 | VLDB |
| 8 | 865 | Natural language to SQL: Where are we today? | 2020 | VLDB |
| 9 | 279 | Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation | 2024 | VLDB |
| 10 | 10,211 | Comparison and Analysis of Value Linking in Text-to-SQL Systems [Experiments & Analysis] | 2026 | SIGMOD |