Last Updated: November 21, 2025
Neo4j
Graph database management system
Core Concepts
| Item | Description |
|---|---|
Node
|
Entity with properties |
Relationship
|
Connection between nodes |
Property
|
Key-value data on nodes/relationships |
Label
|
Node type/category |
Cypher
|
Query language for graphs |
Path
|
Sequence of connected nodes |
Cypher Examples
// Create nodes
CREATE (p:Person {name: 'Alice', age: 30})
CREATE (c:Company {name: 'TechCorp'})
// Create relationship
CREATE (p)-[:WORKS_AT {since: 2020}]->(c)
// Query patterns
MATCH (p:Person)-[:WORKS_AT]->(c:Company)
WHERE p.age > 25
RETURN p.name, c.name
// Find shortest path
MATCH path = shortestPath(
(p1:Person {name: 'Alice'})-[*]-(p2:Person {name: 'Bob'})
)
RETURN pathCommon Patterns
| Item | Description |
|---|---|
(n)
|
Match any node |
(n:Label)
|
Match node with label |
-[r]->
|
Match directed relationship |
-[r:TYPE]->
|
Match relationship by type |
[*1..3]
|
Variable length path (1-3 hops) |
Best Practices
- Use indexes on frequently queried properties
- Design relationships to match query patterns
- Use EXPLAIN and PROFILE for query optimization
- Limit result sets with LIMIT clause
💡 Pro Tips
Quick Reference
Use graph algorithms for complex path analysis