This blog post explores the reading of JSON datasets and the JSON object type in ClickHouse, a popular open-source relational database management system. It demonstrates how ClickHouse can automatically infer column types from JSON data, allowing for flexible schema design. The post showcases the JSONAsObject format, which treats each row as a JSON object, enabling automatic creation of sub-columns with inferred types. This allows for efficient querying and storage of semi-structured data. However, the post also notes limitations, such as the inability to use JSON columns as primary keys, and provides workarounds, including separating structured fields from JSON columns. The experimental nature of this feature is highlighted, and users are encouraged to provide feedback as it moves towards production readiness.