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    <abstract>Large Language Models (LLMs) can automate or substitute different types of tasks in the software engineering process. This study evaluates the resource utilization and accuracy of LLM in interpreting and executing natural language queries against traditional SQL within relational database management systems. We empirically examine the resource utilization and accuracy of nine LLMs varying from 7 to 34 Billion parameters, including Llama2 7B, Llama2 13B, Mistral, Mixtral, Optimus-7B, SUS-chat-34B, platypus-yi-34b, NeuralHermes-2.5-Mistral-7B and Starling-LM-7B-alpha, using a small transaction dataset. Our findings indicate that using LLMs for database queries incurs significant energy overhead (even small and quantized models), making it an environmentally unfriendly approach. Therefore, we advise against replacing relational databases with LLMs due to their substantial resource utilization.</abstract>
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%0 Conference Proceedings
%T Can LLMs substitute SQL? Comparing Resource Utilization of Querying LLMs versus Traditional Relational Databases
%A Zhang, Xiang
%A Khedri, Khatoon
%A Rawassizadeh, Reza
%Y Fu, Xiyan
%Y Fleisig, Eve
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%@ 979-8-89176-097-4
%F zhang-etal-2024-llms-substitute
%X Large Language Models (LLMs) can automate or substitute different types of tasks in the software engineering process. This study evaluates the resource utilization and accuracy of LLM in interpreting and executing natural language queries against traditional SQL within relational database management systems. We empirically examine the resource utilization and accuracy of nine LLMs varying from 7 to 34 Billion parameters, including Llama2 7B, Llama2 13B, Mistral, Mixtral, Optimus-7B, SUS-chat-34B, platypus-yi-34b, NeuralHermes-2.5-Mistral-7B and Starling-LM-7B-alpha, using a small transaction dataset. Our findings indicate that using LLMs for database queries incurs significant energy overhead (even small and quantized models), making it an environmentally unfriendly approach. Therefore, we advise against replacing relational databases with LLMs due to their substantial resource utilization.
%U https://aclanthology.org/2024.acl-srw.51/
%P 465-472

Markdown (Informal)

[Can LLMs substitute SQL? Comparing Resource Utilization of Querying LLMs versus Traditional Relational Databases](https://aclanthology.org/2024.acl-srw.51/) (Zhang et al., ACL 2024)

• Can LLMs substitute SQL? Comparing Resource Utilization of Querying LLMs versus Traditional Relational Databases (Zhang et al., ACL 2024)

ACL

• Xiang Zhang, Khatoon Khedri, and Reza Rawassizadeh. 2024. Can LLMs substitute SQL? Comparing Resource Utilization of Querying LLMs versus Traditional Relational Databases. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 465–472, Bangkok, Thailand. Association for Computational Linguistics.