Design and query MongoDB and PostgreSQL schemas for OLTP and analytics.
npx skills add https://github.com/EdgeHunt/EdgeHunt --skill ck-databases-edgehunt
Please help me install this Agent Skill. Skill: ck:databases Source: https://github.com/EdgeHunt/EdgeHunt/tree/main/.claude/skills/databases Command: npx skills add https://github.com/EdgeHunt/EdgeHunt --skill ck-databases-edgehunt
The Databases Skill provides a unified framework for designing robust schemas and crafting effective SQL and NoSQL queries across MongoDB and PostgreSQL, helping you optimize data structures, migrations, and performance.
Design databases and write queries across MongoDB and PostgreSQL to meet transactional and analytical needs.
High-intent search queries and answers about installing and using this skill.
Schema design applies normalization and denormalization trade-offs to optimize PostgreSQL relational models and MongoDB document models for OLTP and analytics workloads. It provides specific guidelines for both transactional and analytical requirements.
Query optimization for SQL and NoSQL involves crafting efficient joins, aggregation pipelines, and indexing strategies to tune performance. It supports cross-database workflows to handle large-scale data retrieval and processing effectively.
Migrating between relational and document models requires mapping PostgreSQL schemas to MongoDB document structures and vice versa. The skill handles cross-database workflows and schema transformations to ensure data integrity during the transition.
Incremental ETL and analytics-ready schemas are supported through dedicated guidelines in analytics.md and incremental-etl.md. It helps structure data specifically for OLAP querying and analytical processing alongside standard transactional operations.
Indexing improves MongoDB query speed by optimizing document lookups, while aggregation pipelines process and transform data across multiple stages. The skill provides best practices to apply both techniques appropriately for specific query patterns.
Cross-database workflows utilize psycopg2 for PostgreSQL and pymongo for MongoDB connections to execute concurrent SQL and NoSQL operations. This allows simultaneous relational and document database interactions within a single integrated environment.
TNHoang2708Manage MongoDB and PostgreSQL databases with schema design, querying, and performance tuning.
felix-howardDesign database schemas and write SQL and MongoDB queries.
lhlValidate Reality Check database schema, referential integrity, and duplicates.
miles990Design schemas, query, and optimize PostgreSQL, MongoDB, Redis, and Prisma databases.
