Graph data models are fundamental structures used to represent and store data in the form of graphs, which consist of nodes (or vertices) and edges (or links). This model is particularly effective for illustrating relationships and connections among various data entities, making it invaluable in domains such as social networks, recommendation systems, logistics, biological networks, and more. Here's an overview of key concepts and types of graph data models:

Key Concepts:
Nodes (Vertices): Represent entities or objects within the graph, such as people in a social network, stations in a transportation map, or proteins in biological networks.
Edges (Links): Depict the relationships or interactions between nodes. Edges can be directed (indicating a one-way relationship) or undirected (indicating a mutual relationship).
Properties: Both nodes and edges can have properties (key-value pairs) that provide additional information, such as weights, types, or other attributes relevant to the application.