%% generate tags start %% #software-engineering %% generate tags end %% #software-engineering/database A graph database is a type of database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. The key concept is the use of graph theory to store, map, and query relationships. Here's how it differs from SQL (relational) and NoSQL databases: 1. **SQL (Relational Databases)**: Uses tables to store data. The relationships are defined through keys and foreign keys. Ideal for structured data with consistent schema but can be less flexible for complex relationships or hierarchical data. 2. **NoSQL Databases**: A broad category that includes various types of databases like document, key-value, wide-column, and graph databases. NoSQL databases are generally more flexible, allowing for varied data structures and are often more scalable. 3. ==**Graph Databases (A type of NoSQL)**: Specifically optimized to capture relationships in data. Nodes represent entities, and edges represent the relationships between them. Properties can be added to both nodes and edges.== Graph databases excel in scenarios where relationships and connections are essential, such as social networks, recommendation engines, and network analysis. In essence, graph databases are a subset of NoSQL databases, specialized for handling complex relationships and interconnected data in an efficient and intuitive way.