Neo4j

Neo4j is a graph database management system (GDBMS) that uses a graph structure to store, manage, and query highly connected data. Unlike relational databases that use tables, Neo4j represents data as nodes (entities) and relationships (connections between entities).

Key Features of Neo4j:

• Graph-based storage: Data is stored as nodes and relationships instead of tables.
• Uses Cypher Query Language (CQL): A specialized query language optimized for graphs.
• Highly optimized for traversing relationships: Queries run efficiently even on large datasets.
• ACID-compliant: Ensures data integrity and reliability.
• Scalable and flexible: Suitable for large, interconnected datasets.

Why Use It?

• Fast Relationship Queries: Unlike SQL JOINs, relationships are stored directly, reducing query time.
• Highly Connected Data: Ideal for social networks, recommendation engines, and fraud detection.
• Flexible Schema: No predefined schema like relational databases; can evolve over time.
• Intuitive Data Representation: Data is naturally modeled as a graph.

Data Model

Component	Description	Example
Nodes	Represent entities (e.g., Person, Product, City)	(User:Person {name: "Alice"})
Relationships	Define how nodes connect (e.g., FRIEND, PURCHASED)	(:Person)-[:FRIEND]->(:Person)
Properties	Key-value pairs storing data inside nodes and relationships	{age: 30, city: "Berlin"}
Labels	Categorize nodes (e.g., Person, Company, Movie)	(:Movie {title: "Inception"})

Cypher Query Language (CQL)

Creating Nodes

CREATE (:Person {name: "Alice", age: 30})

Creating Relationships

MATCH (a:Person {name: "Alice"}), (b:Person {name: "Bob"})
CREATE (a)-[:FRIEND]->(b)

Any Person named Alice and any Person named Bob are now declared as friends

Querying Data

MATCH (p:Person)-[:FRIEND]->(friend)
WHERE p.name = "Alice"
RETURN friend.name

Find all friends of Alice

Updating Data

MATCH (p:Person {name: "Alice"})
SET p.age = 31

Deleting Nodes & Relationships

MATCH (p:Person {name: "Alice"})-[r:FRIEND]->(b)
DELETE r, p