Graph Databases: Modeling Complex Relationships
Comprehensive guide to graph databases, Neo4j, property graphs, and building connected data applications
Comprehensive guide to graph databases, Neo4j, property graphs, and building connected data applications
Learn the fundamentals of Neo4j including nodes, relationships, labels, properties, and Cypher query language for graph data modeling.
Leverage Neo4j for AI applications including knowledge graph construction, vector embeddings, GraphRAG pipelines, and machine learning feature engineering.
Deep dive into Neo4j architecture: storage engine, property files, relationship traversal, indexes, caching, and query execution pipeline.
Master Neo4j operations including installation, configuration, backup, recovery, monitoring, clustering, and production best practices.
Explore the latest Neo4j developments including version 5.x features, GraphRAG, multi-database support, graph machine learning, and the evolving graph ecosystem.
Explore real-world Neo4j use cases including social networks, fraud detection, recommendation engines, network management, and knowledge graphs.
Complete guide to graph databases for relationship-heavy data. Learn Neo4j, ArangoDB, and graph query patterns with practical examples and performance optimization.