Graph Algorithms

Graph algorithms unlock insights hidden in the structure of connected data. Neo4j provides the Graph Data Science (GDS) library — a comprehensive collection of algorithms for pathfinding, centrality, community detection, similarity, and more.

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The Graph Data Science (GDS) Library

GDS is a Neo4j plugin that provides:

• 65+ graph algorithms across multiple categories
• Graph projections — in-memory copies of your data optimised for algorithm execution
• Execution modes — stream, mutate, write, or estimate
• ML pipelines — link prediction and node classification

Installation

Environment	Method
Neo4j Desktop	Install from the Plugins tab
Neo4j AuraDS	Pre-installed
Docker	Use the GDS-enabled Docker image
Server	Download and install the GDS plugin

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Graph Projections

Before running algorithms, you project a subgraph into memory:

// Native projection
CALL gds.graph.project(
  'social-graph',        // projection name
  'Person',              // node labels
  'FRIENDS_WITH'         // relationship types
)

Projection options