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2025-11-30 08:24:11 +08:00

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cloudflare-d1 Build with D1 serverless SQLite database on Cloudflare's edge. Use when: creating databases, writing SQL migrations, querying D1 from Workers, handling relational data, or troubleshooting D1_ERROR, statement too long, migration failures, or query performance issues. MIT

Cloudflare D1 Database

Status: Production Ready Last Updated: 2025-11-23 Dependencies: cloudflare-worker-base (for Worker setup) Latest Versions: wrangler@4.50.0, @cloudflare/workers-types@4.20251121.0

Recent Updates (2025):

  • Nov 2025: Jurisdiction support (data localization compliance), remote bindings GA (wrangler@4.37.0+), automatic resource provisioning
  • Sept 2025: Automatic read-only query retries (up to 2 attempts), remote bindings public beta
  • July 2025: Storage limits increased (250GB → 1TB), alpha backup access removed, REST API 50-500ms faster
  • May 2025: HTTP API permissions security fix (D1:Edit required for writes)
  • April 2025: Read replication public beta (read-only replicas across regions)
  • Feb 2025: PRAGMA optimize support, read-only access permission bug fix
  • Jan 2025: Free tier limits enforcement (Feb 10 start), Worker API 40-60% faster queries

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 = "<UUID>"

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": "<UUID>",             // 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<{ Bindings: Bindings }>();

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 <DATABASE_NAME> <MIGRATION_NAME>

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

# 3. Apply migrations
npx wrangler d1 migrations apply <DATABASE_NAME> --local   # Test locally
npx wrangler d1 migrations apply <DATABASE_NAME> --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": "<UUID>",
      "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:

interface Env { DB: D1Database; }
type Bindings = { DB: D1Database; };
const app = new Hono<{ Bindings: Bindings }>();

prepare() - PRIMARY METHOD (always use for user input):

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

Why: Prevents SQL injection, reusable, better performance, type-safe

Query Result Methods:

  • .all(){ results, meta } - Get all rows
  • .first() → row object or null - Get first row
  • .first('column') → value - Get single column value (e.g., COUNT)
  • .run(){ success, meta } - Execute INSERT/UPDATE/DELETE (no results)

batch() - CRITICAL FOR PERFORMANCE:

const results = await env.DB.batch([
  env.DB.prepare('SELECT * FROM users WHERE user_id = ?').bind(1),
  env.DB.prepare('SELECT * FROM posts WHERE user_id = ?').bind(1)
]);
  • Executes sequentially, single network round trip
  • If one fails, remaining statements don't execute
  • Use for: bulk inserts, fetching related data

exec() - AVOID IN PRODUCTION:

await env.DB.exec('SELECT * FROM users;'); // Only for migrations/maintenance
  • Never use with user input (SQL injection risk)
  • Only use for: migration files, one-off tasks

Query Patterns

Basic CRUD Operations

// CREATE
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;

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

// READ (multiple)
const { results } = await env.DB.prepare('SELECT * FROM users LIMIT ?')
  .bind(10).all();

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

// DELETE
await env.DB.prepare('DELETE FROM users WHERE user_id = ?').bind(userId).run();

// 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();

Pagination Pattern

const page = parseInt(c.req.query('page') || '1');
const 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)
]);

return c.json({
  users: usersResult.results,
  pagination: { page, limit, total: countResult.results[0].total }
});

Batch Pattern (Pseudo-Transactions)

// D1 doesn't support multi-statement transactions, but batch() provides sequential execution
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)
]);
// If any statement fails, batch stops (transaction-like behavior)

Error Handling

Common Error Types:

  • D1_ERROR - General D1 error
  • D1_EXEC_ERROR - SQL syntax error
  • D1_TYPE_ERROR - Type mismatch (undefined instead of null)
  • D1_COLUMN_NOTFOUND - Column doesn't exist

Common Errors and Fixes:

Error Cause Solution
Statement too long Large INSERT with 1000+ rows Break into batches of 100-250 using batch()
Too many requests queued Individual queries in loop Use batch() instead of loop
D1_TYPE_ERROR Using undefined in bind Use null for optional values: .bind(email, bio || null)
Transaction conflicts BEGIN TRANSACTION in migration Remove BEGIN/COMMIT (D1 handles automatically)
Foreign key violations Schema changes break constraints Use PRAGMA defer_foreign_keys = true

Automatic Retries (Sept 2025): D1 automatically retries read-only queries (SELECT, EXPLAIN, WITH) up to 2 times on retryable errors. Check meta.total_attempts in response for retry count.


Performance Optimization

Index Best Practices:

  • Index columns 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 for sorting: CREATE INDEX idx_posts_created_at ON posts(created_at DESC)
  • Multi-column indexes: CREATE INDEX idx_posts_user_published ON posts(user_id, published)
  • Partial indexes: CREATE INDEX idx_users_active ON users(email) WHERE deleted = 0
  • Test with: EXPLAIN QUERY PLAN SELECT ...

PRAGMA optimize (Feb 2025):

CREATE INDEX idx_users_email ON users(email);
PRAGMA optimize;  -- Run after schema changes

Query Optimization:

  • Use specific columns (not SELECT *)
  • Always include LIMIT on large result sets
  • Use indexes for WHERE conditions
  • Avoid functions in WHERE (can't use indexes): WHERE LOWER(email) → store lowercase instead

Local Development

Local vs Remote (Nov 2025 - Remote Bindings GA):

# Local database (automatic creation)
npx wrangler d1 migrations apply my-database --local
npx wrangler d1 execute my-database --local --command "SELECT * FROM users"

# Remote database
npx wrangler d1 execute my-database --remote --command "SELECT * FROM users"

# Remote bindings (wrangler@4.37.0+) - connect local Worker to deployed D1
# Add to wrangler.jsonc: { "binding": "DB", "remote": true }

Local Database Location: .wrangler/state/v3/d1/miniflare-D1DatabaseObject/<database_id>.sqlite

Seed Local Database:

npx wrangler d1 execute my-database --local --file=seed.sql

Best Practices Summary

Always Do:

  1. Use prepared statements with .bind() for user input
  2. Use .batch() for multiple queries (reduces latency)
  3. Create indexes on frequently queried columns
  4. Run PRAGMA optimize after schema changes
  5. Use IF NOT EXISTS in migrations for idempotency
  6. Test migrations locally before applying to production
  7. Handle errors gracefully with try/catch
  8. Use null instead of undefined for optional values
  9. Validate input before binding to queries
  10. Check meta.rows_written after UPDATE/DELETE

Never Do:

  1. Never use .exec() with user input (SQL injection risk)
  2. Never hardcode database_id in public repos
  3. Never use undefined in bind parameters (causes D1_TYPE_ERROR)
  4. Never fire individual queries in loops (use batch instead)
  5. Never forget LIMIT on potentially large result sets
  6. Never use SELECT * in production (specify columns)
  7. Never include BEGIN TRANSACTION in migration files
  8. Never modify applied migrations (create new ones)
  9. Never skip error handling on database operations
  10. Never assume queries succeed (always check results)

Known Issues Prevented

Issue Description How to Avoid
Statement too long Large INSERT statements exceed D1 limits Break into batches of 100-250 rows
Transaction conflicts BEGIN TRANSACTION in migration files Remove BEGIN/COMMIT (D1 handles this)
Foreign key violations Schema changes break foreign key constraints Use PRAGMA defer_foreign_keys = true
Rate limiting / queue overload Too many individual queries Use batch() instead of loops
Memory limit exceeded Query loads too much data into memory Add LIMIT, paginate results, shard queries
Type mismatch errors Using undefined instead of null Always use null for optional values

Wrangler Commands Reference

# Database management
wrangler d1 create <DATABASE_NAME>
wrangler d1 list
wrangler d1 delete <DATABASE_NAME>
wrangler d1 info <DATABASE_NAME>

# Migrations
wrangler d1 migrations create <DATABASE_NAME> <MIGRATION_NAME>
wrangler d1 migrations list <DATABASE_NAME> --local|--remote
wrangler d1 migrations apply <DATABASE_NAME> --local|--remote

# Execute queries
wrangler d1 execute <DATABASE_NAME> --local|--remote --command "SELECT * FROM users"
wrangler d1 execute <DATABASE_NAME> --local|--remote --file=./query.sql

# Time Travel (view historical data)
wrangler d1 time-travel info <DATABASE_NAME> --timestamp "2025-10-20"
wrangler d1 time-travel restore <DATABASE_NAME> --timestamp "2025-10-20"

Official Documentation


Ready to build with D1! 🚀