Abstract:The research on natural language to SQL (NL2SQL) has high application value. With the maturity of deep learning technology, increasingly more researchers have begun to apply deep learning technology to NL2SQL tasks. This study reviews the research status of NL2SQL in English and Chinese fields and summarizes the datasets and models published by year. Additionally, it compares the characteristics of the four major Chinese NL2SQL datasets and expounds on the basic framework of NL2SQL tasks based on deep learning and typical models for simple single-table problems and complex cross-table problems in Chinese NL2SQL fields. Finally, the commonly adopted model evaluation methods are introduced, and future research directions are put forward.