neumann-schema

What problem does it solve?

This skill guides product and engineering teams to design Neumann data models that combine relational tables, graph nodes and edges, and vector embeddings so applications can store, query, and reason across structured, relational, graph, and semantic data without moving data between systems.

Core Features & Use Cases

• Engine guidance: When to choose relational tables, graph nodes/edges, or vector embeddings based on query patterns and data shape.
• Cross-engine linking: Patterns and best practices for keeping a single identifier across tables, nodes, and embeddings or using atomic ENTITY CREATE operations.
• Practical schemas: Example blueprints for RAG applications, agent memory, and knowledge graphs that show table definitions, node/edge layouts, and embedding key strategies.

Quick Start

Design a Neumann schema for a user profile that combines relational columns, a graph node for relationships, and a vector embedding for semantic search.