drizzle-orm-patterns▌
giuseppe-trisciuoglio/developer-kit · updated Jun 2, 2026
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Expert guide for building type-safe database applications with Drizzle ORM. Covers schema definition, relations, queries, transactions, and migrations for all supported databases.
Drizzle ORM Patterns
Overview
Expert guide for building type-safe database applications with Drizzle ORM. Covers schema definition, relations, queries, transactions, and migrations for all supported databases.
When to Use
- Defining database schemas with tables, columns, and constraints
- Creating relations between tables (one-to-one, one-to-many, many-to-many)
- Writing type-safe CRUD queries
- Implementing complex joins and aggregations
- Managing database transactions with rollback
- Setting up migrations with Drizzle Kit
- Working with PostgreSQL, MySQL, SQLite, MSSQL, or CockroachDB
Quick Reference
| Database | Table Function | Import |
|---|---|---|
| PostgreSQL | pgTable() |
drizzle-orm/pg-core |
| MySQL | mysqlTable() |
drizzle-orm/mysql-core |
| SQLite | sqliteTable() |
drizzle-orm/sqlite-core |
| MSSQL | mssqlTable() |
drizzle-orm/mssql-core |
| Operation | Method | Example |
|---|---|---|
| Insert | db.insert() |
db.insert(users).values({...}) |
| Select | db.select() |
db.select().from(users).where(eq(...)) |
| Update | db.update() |
db.update(users).set({...}).where(...) |
| Delete | db.delete() |
db.delete(users).where(...) |
| Transaction | db.transaction() |
db.transaction(async (tx) => {...}) |
Instructions
- Identify your database dialect - Choose PostgreSQL, MySQL, SQLite, MSSQL, or CockroachDB
- Define your schema - Use the appropriate table function (pgTable, mysqlTable, etc.)
- Set up relations - Define relations using
relations()ordefineRelations() - Initialize the database client - Create your Drizzle client with proper credentials
- Write queries - Use the query builder for type-safe CRUD operations
- Handle transactions - Wrap multi-step operations in transactions when needed
- Set up migrations - Configure Drizzle Kit for schema management
Examples
Example 1: Basic Schema and Query
import { pgTable, serial, text } from 'drizzle-orm/pg-core';
import { drizzle } from 'drizzle-orm/node-postgres';
import { eq } from 'drizzle-orm';
export const users = pgTable('users', {
id: serial('id').primaryKey(),
name: text('name').notNull(),
email: text('email').notNull().unique(),
});
const db = drizzle(process.env.DATABASE_URL);
const [user] = await db.select().from(users).where(eq(users.id, 1));
Example 2: CRUD Operations
import { eq } from 'drizzle-orm';
// Insert
const [newUser] = await db.insert(users).values({
name: 'John',
email: '[email protected]',
}).returning();
// Update
await db.update(users)
.set({ name: 'John Updated' })
.where(eq(users.id, 1));
// Delete
await db.delete(users).where(eq(users.id, 1));
Example 3: Transaction with Rollback
await db.transaction(async (tx) => {
const [from] = await tx.select().from(accounts)
.where(eq(accounts.userId, fromId));
if (from.balance < amount) {
tx.rollback();
}
await tx.update(accounts)
.set({ balance: sql`${accounts.balance} - ${amount}` })
.where(eq(accounts.userId, fromId));
});
See references/transactions.md for advanced transaction patterns.
Best Practices
- Type Safety: Always use TypeScript and leverage
$inferInsert/$inferSelect - Relations: Define relations using the relations() API for nested queries
- Transactions: Use transactions for multi-step operations that must succeed together
- Migrations: Use
generate+migratein production,pushfor development - Indexes: Add indexes on frequently queried columns and foreign keys
- Soft Deletes: Use
deletedAttimestamp instead of hard deletes when possible - Pagination: Use cursor-based pagination for large datasets
- Query Optimization: Use
.limit()and.where()to fetch only needed data
Constraints and Warnings
- Foreign Key Constraints: Always define references using arrow functions
() => table.columnto avoid circular dependency issues - Transaction Rollback: Calling
tx.rollback()throws an exception - use try/catch if needed - Returning Clauses: Not all databases support
.returning()- check your dialect compatibility - Batch Operations: Large batch inserts may hit database limits - chunk into smaller batches
- Migrations in Production: Always test migrations in staging before applying to production
References
Core Concepts
- references/schema-definition.md - Complete schema definition for all databases (PostgreSQL, MySQL, SQLite), column types, indexes, and constraints
- references/relations.md - One-to-one, one-to-many, many-to-many relations with v1 and v2 syntax
- references/queries-joins-aggregations.md - CRUD operations, query operators, joins, aggregations, and pagination
Advanced Topics
- references/transactions.md - Transaction patterns, rollback handling, nested transactions
- references/migrations.md - Drizzle Kit configuration, CLI commands, migration workflow
- references/common-patterns.md - Soft delete, upsert, batch operations, full-text search, audit trails
How to use drizzle-orm-patterns on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add drizzle-orm-patterns
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches drizzle-orm-patterns from GitHub repository giuseppe-trisciuoglio/developer-kit and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate drizzle-orm-patterns. Access the skill through slash commands (e.g., /drizzle-orm-patterns) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★36 reviews- ★★★★★Amelia Mehta· Dec 12, 2024
Keeps context tight: drizzle-orm-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ganesh Mohane· Dec 8, 2024
drizzle-orm-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Neel Malhotra· Dec 8, 2024
I recommend drizzle-orm-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Advait Okafor· Dec 4, 2024
drizzle-orm-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Rahul Santra· Nov 27, 2024
Keeps context tight: drizzle-orm-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Neel Chawla· Nov 27, 2024
Useful defaults in drizzle-orm-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Charlotte Ghosh· Nov 3, 2024
drizzle-orm-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Charlotte Bhatia· Oct 22, 2024
drizzle-orm-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Pratham Ware· Oct 18, 2024
We added drizzle-orm-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Naina Lopez· Oct 18, 2024
Registry listing for drizzle-orm-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
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