Neo4j Virtual Graph
(Available now in preview)
Run graph queries on your existing datalake with no ETL
Layer graph queries onto your existing data and start discovering new insights in just a few hours, all on the world’s leading graph intelligence platform
No data movement required
Add graph intelligence on top of your existing data infrastructure with no ETL
Get started quickly
See value before major investment and go from deployment to results in days
Built-in graph intelligence
Explore and discover insights with 65+ graph algorithms and point-and-click tools
Demo
Virtual Graph in action
See how to find circular payments using graph capabilities without having to move data out of Snowflake.
Capabilities
Get graph powered insights with Neo4j Virtual Graph
Uncover hidden relationships and patterns in your data with graph queries running directly on your warehouse, all without disrupting the infrastructure you’ve already invested in
Work across your entire data estate by running composite queries directly against Snowflake, Databricks, Fabric, or any SQL database
Discover new insights with 65+ graph algorithms directly on your warehouse data, such as community detection, centrality, pathfinding, and more
Move faster from data modeling to query execution with GenAI natively integrated at every step, including text2cypher and automated schema design
Use cases
Get graph powered insights with Neo4j Virtual Graph
Knowledge Graphs
Access deep, dynamic context by connecting your data in knowledge graphs across your entire data estate, without moving any data. You can quickly design, implement, and evolve your knowledge graph.
Fraud detection and analytics
Real-time analysis of data relationships is essential to uncovering fraud rings and other sophisticated scams before fraudsters and criminals cause lasting damage. Use simple graph queries to naturally uncover the fraud structures criminals use to hide, all while keeping your data in place.
Ground LLMs with GraphRAG
Discover a smarter way to build GenAI apps with GraphRAG. By combining knowledge graphs and vector search, GraphRAG infuses your AI with deep context and multi-hop reasoning for more accurate, relevant, and explainable results.
Context graph
Large language models are only as good as the context behind them. By combining knowledge graphs and vector search, you can give your AI deep, connected context, enabling more accurate, relevant, and explainable results than standard retrieval alone can provide.
Loved by devs. Deployed worldwide.
1,700+ organizations build on Neo4j for data breakthroughs. Build with a comprehensive platform for modeling, managing, and retrieving context.
Works seamlessly with your tech stack
Neo4j integrates with leading technology providers
Resources
Learn more about Neo4j, graph databases, GenAI, analytics and more
