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Chapter 6: Graph Operations and Relationship Modeling

Overview

Graph operations and relationship modeling are fundamental to modern applications, enabling complex data relationships, social networks, recommendation systems, and knowledge graphs. Vektagraf provides a comprehensive graph system that seamlessly integrates with its object-centric design, allowing you to model and traverse relationships naturally while maintaining performance and security. This chapter covers graph concepts, relationship modeling patterns, traversal operations, and advanced graph algorithms.

Learning Objectives

By the end of this chapter, you will be able to:

  • Model complex relationships using Vektagraf's graph system
  • Perform efficient graph traversals and pathfinding operations
  • Implement social network features with relationship-based queries
  • Build recommendation systems using graph algorithms
  • Optimize graph operations for performance and scalability
  • Secure graph operations with relationship-level access control
  • Analyze graph structures and extract insights from connected data

Prerequisites

  • Completed Chapter 4: Database Operations and Transactions
  • Completed Chapter 5: Vector Search and Similarity Operations
  • Basic understanding of graph theory concepts (nodes, edges, paths)
  • Familiarity with social network and recommendation system concepts

Core Concepts

Graph Model in Vektagraf

Vektagraf implements a property graph model where:

  • Nodes represent entities with properties and labels
  • Edges represent relationships with types and properties
  • Labels categorize nodes (e.g., "User", "Product", "Document")
  • Types categorize edges (e.g., "FRIENDS_WITH", "PURCHASED", "AUTHORED")
  • Properties store additional data on both nodes and edges

Object-Graph Integration

Unlike traditional graph databases, Vektagraf automatically creates graph nodes for your objects:

// When you save an object, a graph node is automatically created
final user = User(
  name: 'Alice Johnson',
  email: 'alice@example.com',
  interests: ['technology', 'music'],
);

final userId = await users.save(user);
// Graph node created automatically with labels: ['User']
// Properties: {name: 'Alice Johnson', email: 'alice@example.com', ...}

Relationship Types

Vektagraf supports various relationship patterns:

  1. One-to-One: User ↔ Profile
  2. One-to-Many: User → Posts
  3. Many-to-Many: Users ↔ Groups
  4. Hierarchical: Categories → Subcategories
  5. Temporal: Events → Timeline
  6. Weighted: Friendship strength, similarity scores
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