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jikime-domain-database

Manage and optimize PostgreSQL, MongoDB, Redis, and Oracle database systems.

5|1|Updated Jan 24, 2026
Search Tags:#performance#database#postgresql#redis#oracle#mongodb#data patterns
One-click install
npx skills add https://github.com/jikime/jikime-adk --skill jikime-domain-database
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: jikime-domain-database
Source: https://github.com/jikime/jikime-adk/tree/main/templates/.claude/skills/jikime-domain-database
Command: npx skills add https://github.com/jikime/jikime-adk --skill jikime-domain-database

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the complexity of managing and optimizing various database systems, from traditional relational databases like PostgreSQL and Oracle to NoSQL solutions like MongoDB and in-memory stores like Redis, ensuring efficient data handling and performance in modern applications.

Core Features & Use Cases

  • Multi-Database Support: Comprehensive expertise in PostgreSQL, MongoDB, Redis, and Oracle.
  • Performance Optimization: Advanced techniques for query tuning, indexing, and scaling.
  • Data Modeling & Architecture: Designing robust schemas and implementing polyglot persistence patterns.
  • Use Case: Integrate user data from a PostgreSQL relational database, profile information from a MongoDB document store, and real-time status from a Redis cache into a unified user profile view.

Quick Start

Initialize a DatabaseManager instance and configure connections for PostgreSQL, MongoDB, and Redis, then query user data across all configured databases.

Frequently Asked Questions about jikime-domain-database

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

FAQPage Schema
How do I optimize PostgreSQL query performance and indexing strategies?▼

PostgreSQL query performance optimization involves advanced query tuning, indexing strategies, and scaling techniques. This Skill provides expert guidance on refining indexing strategies and tuning queries to ensure efficient data handling in modern applications.

What is polyglot persistence and how does it manage data across MongoDB, Redis, and Oracle?▼

Polyglot persistence is an architecture pattern using multiple data stores for diverse data needs. It manages synchronization across MongoDB, Redis, Oracle, and PostgreSQL, integrating relational, document, and in-memory data into unified views.

How do I synchronize real-time status from a Redis cache with user data in a relational database?▼

Synchronizing Redis cache with relational databases involves configuring connections across both data stores and querying user data simultaneously. This enables a unified user profile view combining real-time status with persistent relational data.

Can I scale NoSQL and relational databases together for modern application data patterns?▼

Scaling NoSQL and relational databases together is supported through advanced data patterns and polyglot persistence. This approach allows modern applications to leverage diverse database systems like MongoDB and Oracle for efficient data handling.

When should I not use a single database type for modern application data storage?▼

A single database type is insufficient when applications require diverse data handling, such as combining relational data, document stores, and in-memory caches. Polyglot persistence across multiple database systems addresses these complex performance and scaling needs.

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