Why Neo4j for
Knowledge Graphs
Access deep, dynamic context by connecting your data in knowledge graphs. You can quickly design, implement, and evolve your knowledge graph with Neo4j.
Easy to Model
Design data models that naturally mirror real-world relationships and business logic
Simple to Implement
Move seamlessly from conceptual to physical data model with a property graph
Fast to Code
Develop faster using fewer lines of code with an intuitive and expressive query language
Quick to Update
Adapt to new business requirements with a dev-friendly schema designed for flexibility
Free Guide
Building Knowledge Graphs: A Practitioner’s Guide
What is a Knowledge Graph?
A knowledge graph is a design pattern for storing, organizing, and accessing interrelated data entities, including their semantic relationships. With knowledge graphs, you can better understand your data and build more intelligent applications.
Capabilities
Build With Knowledge Graphs
Represent structured, semi-structured, and unstructured data and their relationships naturally using nodes, relationships, and properties. Eliminate the translation from conceptual to physical models.
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Introduce new data, properties, and relationships without rebuilding the database or modifying application code.
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Write concise, flexible queries with fewer lines of code, tapping into powerful features like quantified path patterns for efficient graph traversal and pattern matching.
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Enrich your knowledge graphs with 65+ production-ready algorithms – including node embeddings, similarity metrics, and community detection – to power intelligent apps and improve decisions.
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Achieve up to 1000x faster queries versus relational and non-native graph databases. Neo4j’s native graph architecture eliminates complex joins and optimizes execution for rapid results.
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Integrate knowledge graphs seamlessly into your existing data ecosystem. Build on Neo4j with native drivers, connectors, and no-code import tools.
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Knowledge Graphs: Enabling Intelligent Apps
Detect Fraud Faster With Fewer False Positives
Identify complex fraud patterns and high-risk entities using knowledge graphs. Connect disparate data across your business to reveal connections to bad actors and suspicious activities. Analyze billions of data connections to spot sophisticated fraud schemes, reduce false positives, and protect your business from financial losses—all in real time.
Understand Your Customers Better
Unify siloed data to create a complete view of your customers in a knowledge graph. Link customer interactions, preferences, and behaviors across multi-channel touchpoints to gain a deep understanding of each individual. With this rich context, you can personalize experiences, anticipate customer needs, and build strong, lasting customer relationships.
Deliver More Relevant Search Results With GenAI
Deliver a better search experience with GenAI-powered semantic search. Applications built with GenAI and knowledge graphs understand user intent, surface relevant results, and provide contextual recommendations. This results in a more intuitive and satisfying search experience.
Loved by Devs. Deployed Worldwide.
1,700+ organizations build with Neo4j-powered knowledge graphs. Read their stories.
The Buzz is Real
“The synergy between knowledge graphs and generative AI serves as a game-changer for businesses, driving transformative impacts across various organizational functions.”
“Knowledge graphs provide the perfect complement to LLM-based solutions where high thresholds of accuracy and correctness need to be attained.”
Gartner Research: AI Design Patterns for Knowledge Graphs and Generative AI, June 2023
