Papers › Datrics Text2SQL. A Framework for Natural Language to SQL Query Generation
Datrics Text2SQL. A Framework for Natural Language to SQL Query Generation
Tetiana Gladkykh, Kirykov Kyrylo
Datrics Text2SQL is a Text-to-SQL framework using Retrieval-Augmented Generation (RAG) to enhance accuracy and reliability. By integrating domain knowledge, database structure, and example-based learning, it addresses common SQL generation challenges such as incorrect table selection, faulty joins, and misinterpreted business rules. A knowledge base built from database documentation and successful queries is stored in a vector database, enabling retrieval of relevant context for precise SQL generation. The structured process of knowledge collection, context retrieval, and query generation ensures adaptability to various database schemas and query types.
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