Neo4j is a highly scalable and widely used [[graph database]] management system. It is designed to store, manage, and query large amounts of structured and connected data. Graph databases, in general, are based on the concept of nodes and relationships. In Neo4j, data is stored as nodes (which represent entities) and relationships (which represent connections between the entities). This graph-based data model allows for efficient traversal of complex relationships and provides powerful insights into the relationships within the data. Neo4j offers a powerful query language called [[Cypher]], which is specifically designed for querying graph databases. Cypher allows users to easily express complex graph patterns and perform operations like traversals, filtering, aggregations, and more. Some key features of Neo4j include: 1. ACID compliance: Neo4j ensures the integrity of your data by providing Atomicity, Consistency, Isolation, and Durability. 2. High performance: The graph-based nature of Neo4j enables fast querying even on large datasets with complex relationships. 3. Scalability: Neo4j can handle millions or even billions of nodes and relationships by distributing the workload across multiple machines. 4. Flexibility: The schema-less nature of Neo4j allows for dynamic changes to the data model without any downtime or loss of data. 5. Native graph processing: Neo4j's native storage engine is optimized for storing and processing graph structures efficiently. Neo4j has a wide range of use cases across various industries such as social networking, fraud detection, recommendation systems, network management, knowledge graphs, bioinformatics, and more. It has a vibrant community backing it up with regular updates, extensions, libraries, and support resources. Overall, Neo4j offers an efficient way to store and query connected data in a scalable manner using its powerful graph database capabilities. # References ```dataview Table title as Title, authors as Authors where contains(subject, "Neo4j") ```