Cloudflare D1

Cloudflare D1 Database

Status: Production Ready ✅ Last Updated: 2025-10-21 Dependencies: cloudflare-worker-base (for Worker setup) Latest Versions: wrangler@4.43.0, @cloudflare/workers-types@4.20251014.0

---

Quick Start (5 Minutes)

1. Create D1 Database

# Create a new D1 database
npx wrangler d1 create my-database

# Output includes database_id - save this!
# ✅ Successfully created DB 'my-database'
#
# [[d1_databases]]
# binding = "DB"
# database_name = "my-database"
# database_id = ""

2. Configure Bindings

Add to your wrangler.jsonc:

{
  "name": "my-worker",
  "main": "src/index.ts",
  "compatibility_date": "2025-10-11",
  "d1_databases": [
    {
      "binding": "DB",                    // Available as env.DB in your Worker
      "database_name": "my-database",      // Name from wrangler d1 create
      "database_id": "",             // ID from wrangler d1 create
      "preview_database_id": "local-db"    // For local development
    }
  ]
}

CRITICAL:

• binding is how you access the database in code (env.DB)
• database_id is the production database UUID
• preview_database_id is for local dev (can be any string)
• Never commit real database_id values to public repos - use environment variables or secrets

3. Create Your First Migration

# Create migration file
npx wrangler d1 migrations create my-database create_users_table

# This creates: migrations/0001_create_users_table.sql

Edit the migration file:

-- migrations/0001_create_users_table.sql
DROP TABLE IF EXISTS users;
CREATE TABLE IF NOT EXISTS users (
  user_id INTEGER PRIMARY KEY AUTOINCREMENT,
  email TEXT NOT NULL UNIQUE,
  username TEXT NOT NULL,
  created_at INTEGER NOT NULL,
  updated_at INTEGER
);

-- Create index for common queries
CREATE INDEX IF NOT EXISTS idx_users_email ON users(email);

-- Optimize database
PRAGMA optimize;

4. Apply Migration

# Apply locally first (for testing)
npx wrangler d1 migrations apply my-database --local

# Apply to production when ready
npx wrangler d1 migrations apply my-database --remote

5. Query from Your Worker

// src/index.ts
import { Hono } from 'hono';

type Bindings = {
  DB: D1Database;
};

const app = new Hono();

app.get('/api/users/:email', async (c) => {
  const email = c.req.param('email');

  try {
    // ALWAYS use prepared statements with bind()
    const result = await c.env.DB.prepare(
      'SELECT * FROM users WHERE email = ?'
    )
    .bind(email)
    .first();

    if (!result) {
      return c.json({ error: 'User not found' }, 404);
    }

    return c.json(result);
  } catch (error: any) {
    console.error('D1 Error:', error.message);
    return c.json({ error: 'Database error' }, 500);
  }
});

export default app;

---

D1 Migrations System

Migration Workflow

# 1. Create migration
npx wrangler d1 migrations create  

# 2. List unapplied migrations
npx wrangler d1 migrations list  --local
npx wrangler d1 migrations list  --remote

# 3. Apply migrations
npx wrangler d1 migrations apply  --local   # Test locally
npx wrangler d1 migrations apply  --remote  # Deploy to production

Migration File Naming

Migrations are automatically versioned:

migrations/
├── 0000_initial_schema.sql
├── 0001_add_users_table.sql
├── 0002_add_posts_table.sql
└── 0003_add_indexes.sql

Rules:

• Files are executed in sequential order
• Each migration runs once (tracked in d1_migrations table)
• Failed migrations roll back (transactional)
• Can't modify or delete applied migrations

Custom Migration Configuration

{
  "d1_databases": [
    {
      "binding": "DB",
      "database_name": "my-database",
      "database_id": "",
      "migrations_dir": "db/migrations",        // Custom directory (default: migrations/)
      "migrations_table": "schema_migrations"   // Custom tracking table (default: d1_migrations)
    }
  ]
}

Migration Best Practices

✅ Always Do:

-- Use IF NOT EXISTS to make migrations idempotent
CREATE TABLE IF NOT EXISTS users (...);
CREATE INDEX IF NOT EXISTS idx_users_email ON users(email);

-- Run PRAGMA optimize after schema changes
PRAGMA optimize;

-- Use transactions for data migrations
BEGIN TRANSACTION;
UPDATE users SET updated_at = unixepoch() WHERE updated_at IS NULL;
COMMIT;

❌ Never Do:

-- DON'T include BEGIN TRANSACTION at start (D1 handles this)
BEGIN TRANSACTION;  -- ❌ Remove this

-- DON'T use MySQL/PostgreSQL syntax
ALTER TABLE users MODIFY COLUMN email VARCHAR(255);  -- ❌ Not SQLite

-- DON'T create tables without IF NOT EXISTS
CREATE TABLE users (...);  -- ❌ Fails if table exists

Handling Foreign Keys in Migrations

-- Temporarily disable foreign key checks during schema changes
PRAGMA defer_foreign_keys = true;

-- Make schema changes that would violate foreign keys
ALTER TABLE posts DROP COLUMN author_id;
ALTER TABLE posts ADD COLUMN user_id INTEGER REFERENCES users(user_id);

-- Foreign keys re-enabled automatically at end of migration

---

D1 Workers API

Type Definitions

// Add to env.d.ts or worker-configuration.d.ts
interface Env {
  DB: D1Database;
  // ... other bindings
}

// For Hono
type Bindings = {
  DB: D1Database;
};

const app = new Hono();

prepare() - Prepared Statements (PRIMARY METHOD)

Always use prepared statements for queries with user input.

// Basic prepared statement
const stmt = env.DB.prepare('SELECT * FROM users WHERE user_id = ?');
const bound = stmt.bind(userId);
const result = await bound.first();

// Chained (most common pattern)
const user = await env.DB.prepare('SELECT * FROM users WHERE email = ?')
  .bind(email)
  .first();

Why use prepare():

• ✅ Prevents SQL injection
• ✅ Can be reused with different parameters
• ✅ Better performance (query plan caching)
• ✅ Type-safe with TypeScript

Query Result Methods

.all() - Get All Rows

const { results, meta } = await env.DB.prepare(
  'SELECT * FROM users WHERE created_at > ?'
)
.bind(timestamp)
.all();

console.log(results);  // Array of rows
console.log(meta);     // { duration, rows_read, rows_written }

.first() - Get First Row

// Returns first row or null
const user = await env.DB.prepare('SELECT * FROM users WHERE email = ?')
  .bind('user@example.com')
  .first();

if (!user) {
  return c.json({ error: 'Not found' }, 404);
}

.first(column) - Get Single Column Value

// Returns the value of a specific column from first row
const count = await env.DB.prepare('SELECT COUNT(*) as total FROM users')
  .first('total');

console.log(count);  // 42 (just the number, not an object)

.run() - Execute Without Results

// For INSERT, UPDATE, DELETE
const { success, meta } = await env.DB.prepare(
  'INSERT INTO users (email, username, created_at) VALUES (?, ?, ?)'
)
.bind(email, username, Date.now())
.run();

console.log(meta);  // { duration, rows_read, rows_written, last_row_id }

batch() - Execute Multiple Queries

CRITICAL FOR PERFORMANCE: Use batch() to reduce latency.

// Prepare multiple statements
const stmt1 = env.DB.prepare('SELECT * FROM users WHERE user_id = ?').bind(1);
const stmt2 = env.DB.prepare('SELECT * FROM users WHERE user_id = ?').bind(2);
const stmt3 = env.DB.prepare('SELECT * FROM posts WHERE user_id = ?').bind(1);

// Execute all in one round trip
const results = await env.DB.batch([stmt1, stmt2, stmt3]);

console.log(results[0].results);  // Users query 1
console.log(results[1].results);  // Users query 2
console.log(results[2].results);  // Posts query

Batch Behavior:

• Executes sequentially (in order)
• Each statement commits individually (auto-commit mode)
• If one fails, remaining statements don't execute
• Much faster than individual queries (single network round trip)

Batch Use Cases:

// ✅ Insert multiple rows efficiently
const inserts = users.map(user =>
  env.DB.prepare('INSERT INTO users (email, username) VALUES (?, ?)')
    .bind(user.email, user.username)
);
await env.DB.batch(inserts);

// ✅ Fetch related data in parallel
const [user, posts, comments] = await env.DB.batch([
  env.DB.prepare('SELECT * FROM users WHERE user_id = ?').bind(userId),
  env.DB.prepare('SELECT * FROM posts WHERE user_id = ?').bind(userId),
  env.DB.prepare('SELECT * FROM comments WHERE user_id = ?').bind(userId)
]);

exec() - Execute Raw SQL (AVOID IN PRODUCTION)

// Only for migrations, maintenance, and one-off tasks
const result = await env.DB.exec(`
  SELECT * FROM users;
  SELECT * FROM posts;
`);

console.log(result);  // { count: 2, duration: 5 }

NEVER use exec() for:

• ❌ Queries with user input (SQL injection risk)
• ❌ Production queries (poor performance)
• ❌ Queries that need results (exec doesn't return data)

ONLY use exec() for:

• ✅ Running migration SQL files locally
• ✅ One-off maintenance tasks
• ✅ Database initialization scripts

---

Query Patterns

Basic CRUD Operations

Create (INSERT)

// Single insert
const { meta } = await env.DB.prepare(
  'INSERT INTO users (email, username, created_at) VALUES (?, ?, ?)'
)
.bind(email, username, Date.now())
.run();

const newUserId = meta.last_row_id;

// Bulk insert with batch()
const users = [
  { email: 'user1@example.com', username: 'user1' },
  { email: 'user2@example.com', username: 'user2' }
];

const inserts = users.map(u =>
  env.DB.prepare('INSERT INTO users (email, username, created_at) VALUES (?, ?, ?)')
    .bind(u.email, u.username, Date.now())
);

await env.DB.batch(inserts);

Read (SELECT)

// Single row
const user = await env.DB.prepare('SELECT * FROM users WHERE user_id = ?')
  .bind(userId)
  .first();

// Multiple rows
const { results } = await env.DB.prepare(
  'SELECT * FROM users WHERE created_at > ? ORDER BY created_at DESC LIMIT ?'
)
.bind(timestamp, 10)
.all();

// Count
const count = await env.DB.prepare('SELECT COUNT(*) as total FROM users')
  .first('total');

// Exists check
const exists = await env.DB.prepare('SELECT 1 FROM users WHERE email = ? LIMIT 1')
  .bind(email)
  .first();

if (exists) {
  // Email already registered
}

Update (UPDATE)

const { meta } = await env.DB.prepare(
  'UPDATE users SET username = ?, updated_at = ? WHERE user_id = ?'
)
.bind(newUsername, Date.now(), userId)
.run();

const rowsAffected = meta.rows_written;

if (rowsAffected === 0) {
  // User not found
}

Delete (DELETE)

const { meta } = await env.DB.prepare('DELETE FROM users WHERE user_id = ?')
  .bind(userId)
  .run();

const rowsDeleted = meta.rows_written;

Advanced Queries

Pagination

app.get('/api/users', async (c) => {
  const page = parseInt(c.req.query('page') || '1');
  const limit = parseInt(c.req.query('limit') || '20');
  const offset = (page - 1) * limit;

  const [countResult, usersResult] = await c.env.DB.batch([
    c.env.DB.prepare('SELECT COUNT(*) as total FROM users'),
    c.env.DB.prepare('SELECT * FROM users ORDER BY created_at DESC LIMIT ? OFFSET ?')
      .bind(limit, offset)
  ]);

  const total = countResult.results[0].total as number;
  const users = usersResult.results;

  return c.json({
    users,
    pagination: {
      page,
      limit,
      total,
      pages: Math.ceil(total / limit)
    }
  });
});

Joins

const { results } = await env.DB.prepare(`
  SELECT
    posts.*,
    users.username as author_name,
    users.email as author_email
  FROM posts
  INNER JOIN users ON posts.user_id = users.user_id
  WHERE posts.published = ?
  ORDER BY posts.created_at DESC
  LIMIT ?
`)
.bind(1, 10)
.all();

Transactions (Batch Pattern)

D1 doesn't support multi-statement transactions, but batch() provides sequential execution:

// Transfer credits between users (pseudo-transaction)
await env.DB.batch([
  env.DB.prepare('UPDATE users SET credits = credits - ? WHERE user_id = ?')
    .bind(amount, fromUserId),
  env.DB.prepare('UPDATE users SET credits = credits + ? WHERE user_id = ?')
    .bind(amount, toUserId),
  env.DB.prepare('INSERT INTO transactions (from_user, to_user, amount) VALUES (?, ?, ?)')
    .bind(fromUserId, toUserId, amount)
]);

Note: If any statement fails, the batch stops. This provides some transaction-like behavior.

---

Error Handling

Error Types

try {
  const result = await env.DB.prepare('SELECT * FROM users WHERE user_id = ?')
    .bind(userId)
    .first();
} catch (error: any) {
  // D1 errors have a message property
  const errorMessage = error.message;

  if (errorMessage.includes('D1_ERROR')) {
    // D1-specific error
  } else if (errorMessage.includes('D1_EXEC_ERROR')) {
    // SQL syntax error
  } else if (errorMessage.includes('D1_TYPE_ERROR')) {
    // Type mismatch (e.g., undefined instead of null)
  } else if (errorMessage.includes('D1_COLUMN_NOTFOUND')) {
    // Column doesn't exist
  }

  console.error('Database error:', errorMessage);
  return c.json({ error: 'Database operation failed' }, 500);
}

Common Errors and Fixes

"Statement too long"

// ❌ DON'T: Single massive INSERT
await env.DB.exec(`
  INSERT INTO users (email) VALUES
    ('user1@example.com'),
    ('user2@example.com'),
    ... // 1000 more rows
`);

// ✅ DO: Break into batches
const batchSize = 100;
for (let i = 0; i 
    env.DB.prepare('INSERT INTO users (email) VALUES (?)').bind(u.email)
  );
  await env.DB.batch(inserts);
}

"Too many requests queued"

// ❌ DON'T: Fire off many individual queries
for (const user of users) {
  await env.DB.prepare('INSERT INTO users (email) VALUES (?)').bind(user.email).run();
}

// ✅ DO: Use batch()
const inserts = users.map(u =>
  env.DB.prepare('INSERT INTO users (email) VALUES (?)').bind(u.email)
);
await env.DB.batch(inserts);

"D1TYPEERROR" (undefined vs null)

// ❌ DON'T: Use undefined
await env.DB.prepare('INSERT INTO users (email, bio) VALUES (?, ?)')
  .bind(email, undefined);  // ❌ D1 doesn't support undefined

// ✅ DO: Use null for optional values
await env.DB.prepare('INSERT INTO users (email, bio) VALUES (?, ?)')
  .bind(email, bio || null);

Retry Logic

async function queryWithRetry(
  queryFn: () => Promise,
  maxRetries = 3
): Promise {
  for (let attempt = 0; attempt  setTimeout(resolve, delay));
    }
  }

  throw new Error('Retry logic failed');
}

// Usage
const user = await queryWithRetry(() =>
  env.DB.prepare('SELECT * FROM users WHERE user_id = ?')
    .bind(userId)
    .first()
);

---

Performance Optimization

Indexes

Indexes dramatically improve query performance for filtered columns.

When to Create Indexes

// ✅ Index columns used in WHERE clauses
CREATE INDEX idx_users_email ON users(email);

// ✅ Index foreign keys
CREATE INDEX idx_posts_user_id ON posts(user_id);

// ✅ Index columns used for sorting
CREATE INDEX idx_posts_created_at ON posts(created_at DESC);

// ✅ Multi-column indexes for complex queries
CREATE INDEX idx_posts_user_published ON posts(user_id, published);

Test Index Usage

-- Check if index is being used
EXPLAIN QUERY PLAN SELECT * FROM users WHERE email = 'user@example.com';

-- Should see: SEARCH users USING INDEX idx_users_email

Partial Indexes

-- Index only non-deleted records
CREATE INDEX idx_users_active ON users(email) WHERE deleted = 0;

-- Index only published posts
CREATE INDEX idx_posts_published ON posts(created_at DESC) WHERE published = 1;

PRAGMA optimize

Run after creating indexes or making schema changes:

-- In your migration file
CREATE INDEX idx_users_email ON users(email);
PRAGMA optimize;

Or

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: jackspace
• Source: jackspace/ClaudeSkillz
• License: MIT
• Homepage: http://claudeskillz.jackspace.com/

Install and usage instructions live in the source repository linked above.