Enabling interaction with users in a chatbot environment is an important step toward building natural and intuitive NLIDBs. This chapter explores the problem of multi-turn Text-to-SQL, focusing on its two main subcategories: interactive and conversational Text-to-SQL. For each subcategory, the chapter outlines the core challenges and offers a comprehensive overview of the systems’ architecture. The chapter also presents existing datasets and evaluation metrics, providing a holistic understanding of how progress in the field is assessed. Finally, it presents a set of representative systems for the conversational Text-to-SQL task, illustrating how various design choices are implemented in practice.