Data analysis using graph traversal, recursion, and shortest path

In a recent SurrealDB stream, the focus was on the advanced capabilities of graph data modeling using SurrealDB's multi-model database, which incorporates graph traversal, recursive querying, and shortest path calculations. This approach is particularly advantageous for applications like knowledge graphs in AI, fraud detection, and logistics optimization, as it reflects the natural relational thinking of the human brain better than traditional relational or document databases. SurrealDB's query language, SurrealQL, allows users to create and explore complex data models, such as social networks or corporate hierarchies, using recursive and shortest path algorithms, facilitating insights into interconnected data. The database supports a hybrid model, combining structured records with graph traversal, enabling users to choose between performance optimization and metadata-rich queries. The platform encourages users to experiment with graph modeling and query techniques to unlock powerful data insights and efficiencies.