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Property graph

A property graph is a graph data model in which nodes and the edges connecting them can have labels and key-value properties.

How 2 Manning books explain it

Graph Algorithms for Data Science

A property graph is a graph model in which nodes and relationships can carry properties and relationships connect nodes rather than other relationships.

How it is used
Frames graph modeling as the first step toward querying, descriptive analytics, inferred networks, and graph machine learning.
How deep it goes
Defines LPG components, direction, properties, notation, and modeling choices, then stops short of comparing graph models.
Examples
Uses people, organizations, friendship, employment, fraud, class hierarchies, and Twitter follower, tweet, and retweet networks.
What you can do after
Build it from scratch by translating a domain into labeled nodes, typed relationships, properties, and Cypher representations.

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Knowledge Graphs and LLMs in Action

A labeled property graph is a graph data model in which nodes and edges have labels and properties and represent relationships.

How it is used
Supports knowledge graphs requiring property-rich representations, efficient traversal, path analysis, and relationship-specific metadata.
How deep it goes
Defines nodes, edges, properties, traversal, and RDF contrasts, but stops short of RDF’s advanced semantic capabilities.
Examples
Uses a disease–phenotype annotation whose edge stores source, author, and creation date, queried with Cypher.
What you can do after
Apply it via Cypher to model entities, attach edge provenance, and retrieve relationship properties through graph patterns.

Read how Knowledge Graphs and LLMs in Action explains property graph →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.