d1-drizzle-schema
npx machina-cli add skill jezweb/claude-skills/d1-drizzle-schema --openclawD1 Drizzle Schema
Generate correct Drizzle ORM schemas for Cloudflare D1. D1 is SQLite-based but has important differences that cause subtle bugs if you use standard SQLite patterns. This skill produces schemas that work correctly with D1's constraints.
Critical D1 Differences
| Feature | Standard SQLite | D1 |
|---|---|---|
| Foreign keys | OFF by default | Always ON (cannot disable) |
| Boolean type | No | No — use integer({ mode: 'boolean' }) |
| Datetime type | No | No — use integer({ mode: 'timestamp' }) |
| Max bound params | ~999 | 100 (affects bulk inserts) |
| JSON support | Extension | Always available (json_extract, ->, ->>) |
| Concurrency | Multi-writer | Single-threaded (one query at a time) |
Workflow
Step 1: Describe the Data Model
Gather requirements: what tables, what relationships, what needs indexing. If working from an existing description, infer the schema directly.
Step 2: Generate Drizzle Schema
Create schema files using D1-correct column patterns:
import { sqliteTable, text, integer, real, index, uniqueIndex } from 'drizzle-orm/sqlite-core'
export const users = sqliteTable('users', {
// UUID primary key (preferred for D1)
id: text('id').primaryKey().$defaultFn(() => crypto.randomUUID()),
// Text fields
name: text('name').notNull(),
email: text('email').notNull(),
// Enum (stored as TEXT, validated at schema level)
role: text('role', { enum: ['admin', 'editor', 'viewer'] }).notNull().default('viewer'),
// Boolean (D1 has no BOOL — stored as INTEGER 0/1)
emailVerified: integer('email_verified', { mode: 'boolean' }).notNull().default(false),
// Timestamp (D1 has no DATETIME — stored as unix seconds)
createdAt: integer('created_at', { mode: 'timestamp' }).notNull().$defaultFn(() => new Date()),
updatedAt: integer('updated_at', { mode: 'timestamp' }).notNull().$defaultFn(() => new Date()),
// Typed JSON (stored as TEXT, Drizzle auto-serialises)
preferences: text('preferences', { mode: 'json' }).$type<UserPreferences>(),
// Foreign key (always enforced in D1)
organisationId: text('organisation_id').references(() => organisations.id, { onDelete: 'cascade' }),
}, (table) => ({
emailIdx: uniqueIndex('users_email_idx').on(table.email),
orgIdx: index('users_org_idx').on(table.organisationId),
}))
See references/column-patterns.md for the full type reference.
Step 3: Add Relations
Drizzle relations are query builder helpers (separate from FK constraints):
import { relations } from 'drizzle-orm'
export const usersRelations = relations(users, ({ one, many }) => ({
organisation: one(organisations, {
fields: [users.organisationId],
references: [organisations.id],
}),
posts: many(posts),
}))
Step 4: Export Types
export type User = typeof users.$inferSelect
export type NewUser = typeof users.$inferInsert
Step 5: Set Up Drizzle Config
Copy assets/drizzle-config-template.ts to drizzle.config.ts and update the schema path.
Step 6: Add Migration Scripts
Add to package.json:
{
"db:generate": "drizzle-kit generate",
"db:migrate:local": "wrangler d1 migrations apply DB --local",
"db:migrate:remote": "wrangler d1 migrations apply DB --remote"
}
Always run on BOTH local AND remote before testing.
Step 7: Generate DATABASE_SCHEMA.md
Document the schema for future sessions:
- Tables with columns, types, and constraints
- Relationships and foreign keys
- Indexes and their purpose
- Migration workflow
Bulk Insert Pattern
D1 limits bound parameters to 100. Calculate batch size:
const BATCH_SIZE = Math.floor(100 / COLUMNS_PER_ROW)
for (let i = 0; i < rows.length; i += BATCH_SIZE) {
await db.insert(table).values(rows.slice(i, i + BATCH_SIZE))
}
D1 Runtime Usage
import { drizzle } from 'drizzle-orm/d1'
import * as schema from './schema'
// In Worker fetch handler:
const db = drizzle(env.DB, { schema })
// Query patterns
const all = await db.select().from(schema.users).all() // Array<User>
const one = await db.select().from(schema.users).where(eq(schema.users.id, id)).get() // User | undefined
const count = await db.select({ count: sql`count(*)` }).from(schema.users).get()
Reference Files
| When | Read |
|---|---|
| D1 vs SQLite, JSON queries, limits | references/d1-specifics.md |
| Column type patterns for Drizzle + D1 | references/column-patterns.md |
Assets
| File | Purpose |
|---|---|
| assets/drizzle-config-template.ts | Starter drizzle.config.ts for D1 |
| assets/schema-template.ts | Example schema with all common D1 patterns |
Source
git clone https://github.com/jezweb/claude-skills/blob/main/plugins/cloudflare/skills/d1-drizzle-schema/SKILL.mdView on GitHub Overview
D1 Drizzle Schema generates Drizzle ORM schemas tailored for Cloudflare D1, a SQLite-based engine with unique constraints. It outputs schema files, migrations, type exports, and DATABASE_SCHEMA.md while respecting D1 quirks like always-on foreign keys, 100 parameter limit, and JSON stored as TEXT.
How This Skill Works
Begin by describing the data model, then generate a D1-correct Drizzle schema using patterns such as booleans and timestamps stored as integers, and JSON stored as TEXT. Add relations, export types, configure drizzle, create migration scripts, and finally generate DATABASE_SCHEMA.md documentation to capture the schema.
When to Use It
- When creating a new Cloudflare D1 database and you need a correct Drizzle schema from the start
- When adding tables or evolving an existing D1 schema with proper D1 patterns
- When scaffolding a D1 data layer for a new project or service
- When generating migrations for bulk inserts under D1's 100 parameter limit
- When producing DATABASE_SCHEMA.md documentation alongside the schema and migrations
Quick Start
- Step 1: Describe the data model and relationships (tables, keys, indexes, and constraints).
- Step 2: Generate a D1-correct Drizzle schema using D1 patterns (text for strings, integer booleans, integer timestamps, and text for JSON).
- Step 3: Add migrations, configure drizzle.config.ts, and generate DATABASE_SCHEMA.md for documentation
Best Practices
- Design schemas with D1 quirks in mind: use integer({ mode: 'boolean' }) for booleans and integer({ mode: 'timestamp' }) for datetimes
- Store JSON as TEXT and rely on Drizzle's json handling, avoiding native JSON types
- Always enable and rely on foreign keys in D1 (enforced by the engine)
- Plan migrations with local and remote (Wrangler D1) deployment in mind
- Generate and maintain DATABASE_SCHEMA.md to document the D1 schema alongside code
Example Use Cases
- Scaffolding a new user-service schema for a Cloudflare D1 database with proper foreign keys and JSON fields
- Adding a posts table to an existing D1 database while honoring 100-parameter bulk insert limits
- Exporting types for User and NewUser and wiring up drizzle config for D1 integration
- Creating migration scripts and ensuring local and remote tests run before deploy
- Generating DATABASE_SCHEMA.md to accompany the generated Drizzle schema