The text explores the use of JSON data models in databases like Couchbase and MongoDB, emphasizing the differences between traditional table-based structures and JSON's flexibility. It highlights challenges such as JSON's verbosity and dynamic keys, which often necessitate unique indexing strategies to optimize queries. Couchbase's N1QL query language is presented as a solution, offering advanced query and indexing features to handle flexible and dynamic JSON data effectively. The text discusses specific use cases, including value transformation and dynamic key names, demonstrating how indexes can be created to efficiently query JSON documents despite structural variations. The use of functions like OBJECT_NAMES and OBJECT_PAIRS is illustrated to convert JSON data into arrays for indexing, ensuring rapid execution of queries. Additionally, it mentions the availability of more object functions in N1QL to manage complex data models and references further documentation and resources for in-depth understanding.