Learn CYPHER with Real Code Examples

Cypher excels at querying highly connected data using patterns instead of joins.

Ideal for graph use cases like recommendations, social networks, fraud detection, and knowledge graphs.

Supports MATCH patterns, variable-length traversals, shortest path queries, constraints, and graph algorithms.

MATCH, CREATE, MERGE, DELETE

Graph pattern matching

Property filtering

Path traversals

Aggregation and ordering

Constraints (UNIQUE, EXISTS)

Nodes, Relationships, Properties

Labels and relationship types

MATCH patterns

CREATE, MERGE for graph updates

Constraints (UNIQUE, EXISTS)

Pathfinding queries

Node labels & relationship types

Indexes and constraints

APOC utilities

Stored procedures and triggers

Graph algorithms pipelines

Model graph entities as nodes and relationships

Create constraints for uniqueness

Insert nodes/edges with CREATE/MERGE

Query using MATCH and filters

Optimize with indexes and profiling

Beginner: MATCH, CREATE, simple traversals

Intermediate: MERGE, variable-length paths, constraints

Advanced: graph algorithms, APOC utilities

Expert: optimization, clustering, multi-graph architectures

More expressive than SQL for graph queries

Simpler than Gremlin for beginners

More user-friendly than SPARQL for non-semantic graphs

Better tooling and ecosystem for visualization

2011 – Initial Cypher release by Neo4j

2015 – openCypher initiative introduced

2018 – major performance upgrades

2020–2025 – GDS integration, improved pattern matching

Node: Entity in graph

Relationship: Directed edge

Property: Key-value attribute

Label: Node type

Pattern: ASCII-art graph structure