Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.
Scanned 9/3/2026
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---
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.
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