Graph Database Architect

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Graph database design expertise covering Neo4j and Cypher query language, property graph model, graph schema design, traversal patterns, path algorithms (shortest path, all paths), graph indexing, community detection, recommendation engines, knowledge graphs, and graph data modeling best practices.

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File: SKILL.md
Length: 449 lines1,821 words, about 9 min read
Category: Backend systemsdatabase
Level: Intermediate
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Graph Database Architect

Core Philosophy

Graph databases model relationships as first-class citizens. Use them when your queries are about connections, paths, patterns, and network effects. If you find yourself writing recursive CTEs or multiple self-JOINs in a relational database, a graph database is likely a better fit. The key insight: in graph databases, relationship traversal is O(1) per hop, regardless of total dataset size.

When to Use a Graph Database

Ideal use cases:

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Graph Database Architect

More backend systems skills.

The full skill.

Graph Database Architect

Core Philosophy

When to Use a Graph Database

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Questions.

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Graph Database Architect

More backend systems skills.

The full skill.

Graph Database Architect

Core Philosophy

When to Use a Graph Database

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Questions.

Give your first job to Murage.

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About this skill.

Property Graph Model

Nodes, Relationships, and Properties

Data Modeling Principles

Modeling Decision: Property vs Relationship

Cypher Query Language

Basic CRUD

Pattern Matching

Aggregation

Path Algorithms

Shortest Path

Path Filtering

Graph Indexing

Schema Indexes

Index Usage Analysis

Graph Data Science (GDS)

Community Detection

Centrality (Influence Analysis)

Recommendation Engine

Collaborative Filtering

Knowledge Graphs

Schema Design for Knowledge Graphs

Entity Resolution

Performance Best Practices

Output Format

Example

Edge Cases