6 docs tagged with "Graph Modeling"

When to use generic nesting-driven edges versus explicit typed relationships, and how that choice affects readability, search, and analytics downstream.

Model imported records, transformation steps, derived summaries, and final outputs so every answer can be traced back to its upstream source.

Three common graph shapes — trees, many-to-many networks, and cyclic systems — with guidance on how to query each without flattening away meaning.

Model persistent facts, episodic interactions, and linked reference material as a graph so agents and applications can retrieve and reason over connected context.

Represent durable entities alongside time-stamped events so you can answer both current-state and historical questions without losing lineage.

Map the same product, customer, and order dataset from relational and document mental models into RushDB's graph model, then translate common business questions into multi-hop queries.