Text2VectorSQL: Bridging Text-to-SQL and Vector Search for Unified Natural Language Queries

• URL: http://arxiv.org/abs/2506.23071v1
• Date: Sun, 29 Jun 2025 03:17:42 GMT
• Title: Text2VectorSQL: Bridging Text-to-SQL and Vector Search for Unified Natural Language Queries
• Authors: Zhengren Wang, Bozhou Li, Dongwen Yao, Wentao Zhang,
• Abstract summary: We introduce Text2 - a novel framework unifying Text-to- and vector search.<n>Text2 enables semantic filtering, multi-modal matching, and retrieval acceleration.<n>We develop dedicated Text2 models with synthetic data, demonstrating significant performance improvements over baseline methods.
• Score: 19.61835087779078
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: While Text-to-SQL enables natural language interaction with structured databases, its effectiveness diminishes with unstructured data or ambiguous queries due to rigid syntax and limited expressiveness. Concurrently, vector search has emerged as a powerful paradigm for semantic retrieval, particularly for unstructured data. However, existing VectorSQL implementations still rely heavily on manual crafting and lack tailored evaluation frameworks, leaving a significant gap between theoretical potential and practical deployment. To bridge these complementary paradigms, we introduces Text2VectorSQL, a novel framework unifying Text-to-SQL and vector search to overcome expressiveness constraints and support more diverse and holistical natural language queries. Specifically, Text2VectorSQL enables semantic filtering, multi-modal matching, and retrieval acceleration. For evaluation, we build vector index on appropriate columns, extend user queries with semantic search, and annotate ground truths via an automatic pipeline with expert review. Furthermore, we develop dedicated Text2VectorSQL models with synthetic data, demonstrating significant performance improvements over baseline methods. Our work establishes the foundation for the Text2VectorSQL task, paving the way for more versatile and intuitive database interfaces. The repository will be publicly available at https://github.com/Open-DataFlow/Text2VectorSQL.

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