Run mission-critical applications on the fastest path to graph

With enterprise-grade security and integrity, store and query connected data at unbounded scale so your intelligent applications have what they need when they need it.

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Limitless scale

Scale to 100TB+ across connected datasets.

Rapid insights

Run multi-hop queries up to 1000x faster than relational databases.

Enterprise-grade trust

Enforce security down to individual properties, even at massive scale.

Flexible deployment

Run self-hosted, hybrid, multi-cloud, or fully managed with AuraDB.

Demo

Connected data in minutes

Watch a quick introduction to how Neo4j Graph Database stores and queries connected data.

Capabilities

Scale to 100TB+ across connected datasets with no application or query changes, and query across multiple databases while keeping performance and simplicity intact.

Run multi-hop queries up to 1000x faster than relational databases, and use Cypher Parallel Runtime to execute analytical queries across the graph in parallel.

illustration depicting Neo4j's high performance

Enforce schema-based security and role-based access control down to individual properties, with transactional guarantees that hold across billions of nodes and trillions of relationships.

illustration depicting data node security

Run self-hosted, hybrid, multi-cloud, or fully managed with AuraDB and connect to your stack with Change Data Capture, Kafka, data warehouse, and BI connectors.

illustration depicting cloud environment flexibility

Powerful use cases

Optimize your projects with Graph Database as the foundation

Deliver recommendations in real time

Analyze behavior, purchase history, and connections in real time to recommend the next product, article, or connection your users actually want, not just what's popular.

Manage identity and access at scale

Model users, roles, and permissions as a connected graph, so you can answer access questions instantly and enforce least-privilege policies as your organization grows.

Identify fraud patterns within your data

Accelerate fraud detection across your enterprise and quickly incorporate new data to outpace fraudsters without having to refactor the database or rewrite code.

Ground your AI systems in actual context

Connect structured and unstructured datasets in knowledge graphs, so your AI agents have the right context for making decisions.

Essential GraphRAG book cover

Learn how to feed LLMs context
for complete, relevant GenAI results

Customers

Real-world AI innovations. 
Powered by graph.

“We found that real-time data can only be solved by a graph database.”

Andy Emmonds

Chief Transport Analyst, Transport for London

Partners

Runs on the cloud you already use

Certified on Google Cloud, Microsoft Azure, and AWS, with technology partnerships across the data ecosystem

Microsoft Azure
Google Cloud
AWS
Snowflake
Databricks

Resources

Learn more about Neo4j, graph databases, GenAI, analytics and more

AI’s Compute Scarcity Problem Will Not Be Solved by Data Centers Alone

AI’s Compute Scarcity Problem Will Not Be Solved by Data Centers Alone

Helping companies succeed with AI while avoiding energy waste can address scarcity problems and lower costs.

September 18, 2026: AI’s Compute Scarcity Problem Will Not Be Solved by Data Centers Alone
Connecting the dots in rare disease drug discovery

Connecting the dots in rare disease drug discovery

Graph intelligence is redefining what is possible in drug discovery by making sense of what already exists.

September 14, 2026: Connecting the dots in rare disease drug discovery
What is missing in the fight against AI-enabled fraud

What is missing in the fight against AI-enabled fraud

Connected-data approaches are becoming essential because AI-enabled fraud often leaves patterns across networks, even when individual events appear legitimate.

September 5, 2026: What is missing in the fight against AI-enabled fraud
Data Lineage Matters in the Age of AI, and Graphs Make It Possible

Data Lineage Matters in the Age of AI, and Graphs Make It Possible

As AI grows in India’s digital economy, trust will rely not only on intelligence but also on understanding the origins of data and its connections.

August 31, 2026: Data Lineage Matters in the Age of AI, and Graphs Make It Possible