Database Integration

Database schema design differs by type: PostgreSQL uses normalized relational tables with constraints, while MongoDB uses flexible document structures. This Skill provides schema patterns tailored to each database, showing structural approaches, indexing strategies, and best practices for both SQL and NoSQL systems.

Query optimization varies by database engine. This Skill delivers platform-specific patterns for PostgreSQL, BigQuery, MongoDB, and MySQL, covering indexing, execution plans, aggregation pipelines, and query restructuring to improve performance on each system.

Database migrations manage schema changes safely across environments. This Skill provides migration patterns for PostgreSQL and MySQL, including versioning strategies, rollback approaches, and ORM configuration to automate and track schema updates.

ORMs abstract database differences but work differently per platform. This Skill guides ORM configuration patterns specific to PostgreSQL, MongoDB, and BigQuery, showing how to map objects, handle relationships, and configure connections for each system.

NoSQL integration differs from SQL: MongoDB uses document-oriented patterns, schemaless design, and aggregation pipelines instead of joins. This Skill provides MongoDB-specific patterns for document modeling, querying, indexing, and ORM setup.

SQL databases suit structured, relational data with strong consistency; NoSQL suits flexible, distributed data with eventual consistency. This Skill covers detection and pattern selection for PostgreSQL, MySQL, BigQuery, and MongoDB, helping you pick the right approach for your schema, query, and scaling needs.