Graph Database Architect
Design and optimize graph database schemas, Cypher queries, and production deployments for knowledge graphs, recommendation engines, fraud detection, and network analysis applications.
SupaScore
83.35Best for
- ▸Design property graph schemas for recommendation engines with customer-product relationships
- ▸Write optimized Cypher queries for fraud detection pattern matching across transaction networks
- ▸Architect Neo4j production deployments with clustering and backup strategies
- ▸Model supply chain knowledge graphs with multi-hop dependency analysis
- ▸Implement graph algorithms for social network community detection and PageRank scoring
What you'll get
- ●Complete property graph schema with labeled nodes, directed relationships, and property specifications aligned to query patterns
- ●Optimized Cypher queries with index hints, parameter usage, and performance explanations
- ●Production deployment architecture with clustering configuration, backup strategies, and monitoring setup
Not designed for ↓
- ×Traditional relational database design or SQL optimization
- ×Heavy analytical workloads that require OLAP aggregations
- ×Simple CRUD applications with minimal relationship traversals
- ×Real-time streaming data processing without graph relationships
Clear description of the connected data problem, expected query patterns, data volume estimates, and specific graph use case type (fraud detection, recommendations, knowledge graph, etc.).
Complete graph data model with node/relationship schemas, optimized Cypher queries, index/constraint specifications, and production deployment architecture recommendations.
Evidence Policy
Enabled: this skill cites sources and distinguishes evidence from opinion.
Research Foundation: 7 sources (4 official docs, 2 books, 1 industry frameworks)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
Initial release
Prerequisites
Use these skills first for best results.
Works well with
Need more depth?
Specialist skills that go deeper in areas this skill touches.
Common Workflows
Knowledge Graph Development Pipeline
End-to-end knowledge graph implementation from data discovery through schema design to knowledge extraction
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