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JasonWarrenUK
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data-ontologist

Evaluate data types and access patterns to select relational, graph, or document databases.

5|1|Updated Feb 5, 2026
Search Tags:#schema-design#database-design#graph-databases#polyglot-persistence#data-architecture#relational-databases#document-databases
One-click install
npx skills add https://github.com/JasonWarrenUK/claude-code-config --skill data-ontologist
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-ontologist
Source: https://github.com/JasonWarrenUK/claude-code-config/tree/main/skills/data-ontologist
Command: npx skills add https://github.com/JasonWarrenUK/claude-code-config --skill data-ontologist

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps architects decide when to use relational, graph, or document databases and design polyglot persistence patterns.

Core Features & Use Cases

  • Evaluate data types and access patterns to select the appropriate database type (relational, graph, or document).
  • Provide a framework for choosing between PostgreSQL/Supabase, Neo4j, and MongoDB based on real-world scenarios.
  • Outline integration and data-mass ingestion patterns across databases, including synchronization, migrations, and query composition.

Quick Start

Plan a polyglot persistence strategy for a new microservice, selecting where to store relational data, graph relationships, and document content, and outline the cross-database integration points.

Frequently Asked Questions about data-ontologist

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is polyglot persistence and when do I need it for my data architecture?▼

Polyglot persistence is using multiple database types in a single system. You need it when distinct data structures require different storage, such as combining PostgreSQL for relational data, Neo4j for graph relationships, and MongoDB for document content.

How do I choose between relational, graph, and document databases for my application?▼

Choose databases by evaluating access patterns. Use PostgreSQL for structured relational data, Neo4j for interconnected graph relationships, and MongoDB for flexible document content, matching the database type to your specific data modeling and query requirements.

How do I design cross-database workflows and synchronization across PostgreSQL, Neo4j, and MongoDB?▼

Design cross-database workflows by defining integration points and synchronization patterns across PostgreSQL, Neo4j, and MongoDB. This involves coordinating data consistency, handling data mass ingestion, and planning migrations to keep multiple databases aligned.

Can I use this approach to plan polyglot persistence for a new microservice?▼

Yes, you can plan a polyglot persistence strategy for a new microservice by selecting where to store relational data, graph relationships, and document content, and then outlining the necessary cross-database integration points and data consistency coordination.

What are the limitations of using a multi-database architecture with polyglot persistence?▼

Limitations of a multi-database architecture include the complexity of coordinating data consistency across different systems, managing cross-database migrations, and handling synchronization patterns, which require careful schema evolution and integration planning.

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