Graph Databases (Neo4j, Cypher, Property Graphs)
Navigate complex connected networks: Labeled Property Graphs, Index-Free Adjacency, Declarative Cypher queries, and graph traversal algorithms (Breadth-First, Dijkstra).
01.1. What is a Native Graph Database?
A Graph Database (Neo4j, Amazon Neptune, Memgraph) models data as an interconnected network of:
- Nodes (Vertices / Entities): Represent discrete objects (e.g., Users, Bank Accounts, IP Addresses, Products). Nodes can have one or more Labels (e.g.,
:Person,:Customer). - Relationships (Edges / Links): Directed, named connections between nodes (e.g.,
[:FOLLOWS],[:TRANSFERRED_MONEY],[:PURCHASED]). - Properties: Key-value metadata attached directly to either nodes OR relationships (e.g., a
[:TRANSFERRED_MONEY]relationship can have properties:amount: $5,000, timestamp: 1711550000).
Unlike relational databases where relationships are represented abstractly by foreign key IDs stored in separate tables, graph databases store relationships as first-class physical records on disk.
Labeled Property Graph Model & Multi-Relationship Topology ðļïļ
Labeled Property Graph Model & Multi-Relationship Topology ðļïļ
Nodes (Entities), Directed Typed Edges (Relationships), and Key-Value Properties in a native property graph database.
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