Graph Data Model and Applications

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1. Graph Data Model

Meaning

The graph data model represents data in the form of a graph, consisting of:

• Nodes

• Relationships (Edges)

• Properties

It is designed to efficiently manage highly connected data.

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2. Components of Graph Data Model

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1. Nodes

• Represent entities

• Examples: Person, Product, City

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2. Relationships (Edges)

• Represent connections between nodes

• Always have a direction

• Have a type

Examples:

• FRIEND_OF

• PURCHASED

• LOCATED_IN

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3. Properties

• Key–value pairs attached to nodes or relationships

• Store additional information

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Example

(User)-[FRIEND_OF]->(User)
(User)-[BOUGHT]->(Product)

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3. Features of Graph Data Model

• Relationship-centric

• No joins required

• Schema flexible

• Fast traversal queries

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4. Applications of Graph Data Model

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1. Social Networks

• Users as nodes

• Friendships as relationships

• Examples: Facebook, LinkedIn

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2. Recommendation Systems

• Users and products connected

• Suggest items based on relationships

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3. Fraud Detection

• Detect suspicious connections

• Used in banking and insurance

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4. Network and IT Management

• Devices as nodes

• Connections as edges

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5. Knowledge Graphs

• Stores facts and relationships

• Used in search engines

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5. Advantages of Graph Data Model

• Handles complex relationships efficiently

• Easy data modeling

• High query performance

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6. Limitations

• Complex scaling

• Not ideal for simple data access