Using Schema Functions to Model Your Data in Memgraph

Memgraph, a high-performance graph database, provides schema-related queries and procedures to enhance the understanding and management of data structures within the database. By using configuration flags and specialized procedures like `schema.node_type_properties()` and `schema.rel_type_properties()`, users can obtain detailed insights into node labels, relationship types, and associated properties, aiding efficient query execution. The `meta_util.schema()` procedure offers a comprehensive view of the graph schema, allowing for the retrieval of distinct nodes and relationships, with the option to include property counts for deeper analysis. Additionally, the `llm_util.schema()` procedure caters to large language models by generating graph database schemas in both prompt-ready and raw formats, facilitating their use in applications like LangChain. These tools collectively simplify database management by providing a user-friendly approach to exploring and understanding the data's structure, ensuring effective schema exploration and generation.