--- name: database description: "Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering." category: workflow-bundle risk: safe source: personal date_added: "2026-02-27" --- # Database Workflow Bundle ## Overview Comprehensive database workflow for database design, development, optimization, migrations, and data engineering. Covers SQL, NoSQL, and modern data platforms. ## When to Use This Workflow Use this workflow when: - Designing database schemas - Implementing database migrations - Optimizing query performance - Setting up data pipelines - Managing database operations - Implementing data quality ## Workflow Phases ### Phase 1: Database Design #### Skills to Invoke - `database-architect` - Database architecture - `database-design` - Schema design - `postgresql` - PostgreSQL design - `nosql-expert` - NoSQL design #### Actions 1. Gather requirements 2. Design schema 3. Define relationships 4. Plan indexing strategy 5. Design for scalability #### Copy-Paste Prompts ``` Use @database-architect to design database schema ``` ``` Use @postgresql to design PostgreSQL schema ``` ### Phase 2: Database Implementation #### Skills to Invoke - `prisma-expert` - Prisma ORM - `database-migrations-sql-migrations` - SQL migrations - `neon-postgres` - Serverless Postgres #### Actions 1. Set up database connection 2. Configure ORM 3. Create migrations 4. Implement models 5. Set up seed data #### Copy-Paste Prompts ``` Use @prisma-expert to set up Prisma ORM ``` ``` Use @database-migrations-sql-migrations to create migrations ``` ### Phase 3: Query Optimization #### Skills to Invoke - `database-optimizer` - Database optimization - `sql-optimization-patterns` - SQL optimization - `postgres-best-practices` - PostgreSQL optimization #### Actions 1. Analyze slow queries 2. Review execution plans 3. Optimize indexes 4. Refactor queries 5. Implement caching #### Copy-Paste Prompts ``` Use @database-optimizer to optimize database performance ``` ``` Use @sql-optimization-patterns to optimize SQL queries ``` ### Phase 4: Data Migration #### Skills to Invoke - `database-migration` - Database migration - `framework-migration-code-migrate` - Code migration #### Actions 1. Plan migration strategy 2. Create migration scripts 3. Test migration 4. Execute migration 5. Verify data integrity #### Copy-Paste Prompts ``` Use @database-migration to plan database migration ``` ### Phase 5: Data Pipeline Development #### Skills to Invoke - `data-engineer` - Data engineering - `data-engineering-data-pipeline` - Data pipelines - `airflow-dag-patterns` - Airflow workflows - `dbt-transformation-patterns` - dbt transformations #### Actions 1. Design data pipeline 2. Set up data ingestion 3. Implement transformations 4. Configure scheduling 5. Set up monitoring #### Copy-Paste Prompts ``` Use @data-engineer to design data pipeline ``` ``` Use @airflow-dag-patterns to create Airflow DAGs ``` ### Phase 6: Data Quality #### Skills to Invoke - `data-quality-frameworks` - Data quality - `data-engineering-data-driven-feature` - Data-driven features #### Actions 1. Define quality metrics 2. Implement validation 3. Set up monitoring 4. Create alerts 5. Document standards #### Copy-Paste Prompts ``` Use @data-quality-frameworks to implement data quality checks ``` ### Phase 7: Database Operations #### Skills to Invoke - `database-admin` - Database administration - `backup-automation` - Backup automation #### Actions 1. Set up backups 2. Configure replication 3. Monitor performance 4. Plan capacity 5. Implement security #### Copy-Paste Prompts ``` Use @database-admin to manage database operations ``` ## Database Technology Workflows ### PostgreSQL ``` Skills: postgresql, postgres-best-practices, neon-postgres, prisma-expert ``` ### MongoDB ``` Skills: nosql-expert, azure-cosmos-db-py ``` ### Redis ``` Skills: bullmq-specialist, upstash-qstash ``` ### Data Warehousing ``` Skills: clickhouse-io, dbt-transformation-patterns ``` ## Quality Gates - [ ] Schema designed and reviewed - [ ] Migrations tested - [ ] Performance benchmarks met - [ ] Backups configured - [ ] Monitoring in place - [ ] Documentation complete ## Related Workflow Bundles - `development` - Application development - `cloud-devops` - Infrastructure - `ai-ml` - AI/ML data pipelines - `testing-qa` - Data testing ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.