An In-Depth Benchmarking of Text-to-SQL Systems

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Abstract

Text-to-SQL systems allow users to explore relational databases by posing free-form queries, alleviating the need for using structured languages, such as SQL. Although numerous systems have been developed so far, existing system evaluations lack in rigour. In this work, we build a text-to-SQL benchmark that covers different classes of queries, and we evaluate the effectiveness of several systems in the field. To evaluate system efficiency, we measure execution time and resource consumption for the different query classes. Our comprehensive evaluation aims at filling in a big gap in understanding the capabilities and boundaries of existing systems and it reveals several open challenges.

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APA

Gkini, O., Belmpas, T., Koutrika, G., & Ioannidis, Y. (2021). An In-Depth Benchmarking of Text-to-SQL Systems. In Proceedings of the ACM SIGMOD International Conference on Management of Data (pp. 632–644). Association for Computing Machinery. https://doi.org/10.1145/3448016.3452836

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