15 Types of Graph Algorithms in Neo4j and What They Do

Explore the capabilities and use cases for some of the world's most popular and powerful types of graph algorithms and how they are optimized within Neo4j.

What are graph algorithms? A comprehensive guide Skip to content Neo4j to acquire GraphAware, launch new open-standards intelligence analysis solutions | Read more Menu Search Close Menu Products FULLY-MANAGED AuraDB Store and query connected data at scale Virtual Graph Create and query a knowledge graph on existing data Aura Graph Analytics Run graph algorithms on any data, any cloud Aura Agent Build and deploy context-aware agents fast SELF-MANAGED Graph Database Store connected data with a graph database Graph Data Science Run graph algorithms on connected data Enterprise Studio Securely qu

related reading

• Graph algorithms in Neo4j: PageRankneo4j.com
• A Gentle Introduction to Graph Neural Networksdistill.pub
• Graph database blockchain: How to import Bitcoin blockchain into Neo4jneo4j.com
• Knowledge graph vs. vector database for grounding your LLMneo4j.com
• From good to graph: Choosing the right databaseneo4j.com
• Imperative vs. declarative query languages: Definition & examplesneo4j.com
• Understanding Convolutions on Graphsdistill.pub
• The GraphRAG manifesto: Adding knowledge to GenAIneo4j.com
• Building a graph to map gene variants w/ Neo4j: GeneWeaverneo4j.com
• Connecting the dots in early drug discovery at Novartisneo4j.com
• [2003.02320] Knowledge Graphsarxiv.org
• Fine-tuning vs. RAG for LLMsneo4j.com