Faker.js vs Aphelion: When to Use Each for PostgreSQL Test Data

The Problem Every Developer Faces

You're building a PostgreSQL application. You need test data. You reach for Faker.js—the most popular fake data library with 12 million weekly downloads.

Then you hit the wall: foreign key constraints.

Suddenly, you're writing 200+ lines of manual code to track IDs, insert tables in the right order, and pray you don't hit a circular dependency. Sound familiar?

This article explains:

• What Faker.js can't do for databases
• When to use Faker.js vs. Aphelion
• Real code examples showing the difference
• How to migrate from Faker.js to Aphelion

What Faker.js Can't Do for PostgreSQL

Faker.js is a data generator, not a database seeder. Here's what it can't handle:

1. Foreign Key Constraints

Faker.js doesn't know about your database schema. If orders references users.id, you must:

• Insert users first
• Manually track the returned IDs
• Pass those IDs to orders inserts

For 5 tables, this is annoying. For 50 tables with complex relationships, it's a nightmare.

2. Circular Dependencies

What if users has a manager_id that references users.id? Or employees references departments, and departments references employees.manager_id?

Faker.js has no solution. You need to:

• Insert rows with NULL foreign keys
• Update them after dependent rows exist
• Hope you don't violate NOT NULL constraints

3. Unique Constraints

faker.internet.email() generates random emails, but there's no guarantee they're unique. If your database has a UNIQUE constraint on users.email, you'll get duplicate key errors.

You need to manually track generated values or use sets to prevent duplicates.

4. PostgreSQL-Specific Types

Faker.js doesn't understand:

• ltree (hierarchical labels)
• JSONB with specific schemas
• ARRAY types with constraints
• ENUM types from your database

You're on your own to generate valid data for these.

5. Schema Introspection

Faker.js doesn't connect to your database. You must manually define every table, column, and relationship in your seed script.

When your schema changes, your seed script breaks.

Code Comparison: The Faker.js Way vs. The Aphelion Way

Let's generate test data for a simple e-commerce database with users and orders.

The Faker.js Way (Manual FK Tracking)

// seed.js - Faker.js approach
const { faker } = require('@faker-js/faker');
const { Pool } = require('pg');

const pool = new Pool({
  host: 'localhost',
  database: 'ecommerce',
  user: 'postgres',
  password: 'password'
});

async function seed() {
  try {
    // Step 1: Insert users FIRST (no dependencies)
    const userIds = [];
    console.log('Inserting users...');
    
    for (let i = 0; i < 1000; i++) {
      const result = await pool.query(
        'INSERT INTO users (name, email, created_at) VALUES ($1, $2, $3) RETURNING id',
        [
          faker.person.fullName(),
          faker.internet.email(), // Hope it's unique!
          faker.date.past()
        ]
      );
      userIds.push(result.rows[0].id);
    }
    
    // Step 2: Insert orders (must reference user IDs)
    console.log('Inserting orders...');
    
    for (const userId of userIds) {
      const orderCount = faker.number.int({ min: 1, max: 5 });
      
      for (let i = 0; i < orderCount; i++) {
        await pool.query(
          'INSERT INTO orders (user_id, total, status, created_at) VALUES ($1, $2, $3, $4)',
          [
            userId, // Manually tracked from step 1
            faker.number.float({ min: 10, max: 1000, precision: 0.01 }),
            faker.helpers.arrayElement(['pending', 'shipped', 'delivered']),
            faker.date.past()
          ]
        );
      }
    }
    
    console.log('Seed complete!');
  } catch (error) {
    console.error('Seed failed:', error);
    // Probably a constraint violation you need to debug
  } finally {
    await pool.end();
  }
}

seed();

// Problems with this approach:
// 1. 50+ lines of boilerplate
// 2. Manual ID tracking (userIds array)
// 3. No handling of circular dependencies
// 4. No unique constraint checking
// 5. Breaks when schema changes
// 6. No support for complex types

The Aphelion Way (Automatic)

# One command
aphelion clone postgresql://localhost/ecommerce test_db --rows 1000

# Output:
# 🔍 Introspecting schema...
#    ✓ Found 2 tables
#    ✓ Detected 1 foreign key
#
# 📊 Generating data...
#    ✓ users (1,000 rows)
#    ✓ orders (3,247 rows)
#
# ✅ Generated 4,247 rows in 3 seconds
#    All constraints satisfied. Zero errors.

When to Use Faker.js vs. Aphelion

Use Faker.js For:

• Frontend mocks - Generating fake data for UI prototypes without a database
• Unit test fixtures - Simple objects in memory (no database)
• API mocking - Fake responses for testing API clients
• Single-table data - When you only need one table with no relationships
• Custom formats - When you need very specific fake data formats
• Non-relational data - NoSQL documents, JSON files, etc.

Use Aphelion For:

• PostgreSQL database seeding - Any relational database with foreign keys
• Complex schemas - 10+ tables with multiple relationships
• CI/CD pipelines - Automated test data generation for staging environments
• Healthcare/Fintech - HIPAA or PCI-DSS compliant test data
• Constraint-safe data - When you need guaranteed valid data
• Production-like volumes - Generating millions of rows efficiently

Use Both Together:

Many teams use Aphelion for database seeding and Faker.js for frontend mocks. They complement each other well.

Migrating from Faker.js to Aphelion

If you're currently using Faker.js for database seeding, here's how to switch:

Step 1: Install Aphelion

curl -L https://algomimic.com/api/download/free -o aphelion && chmod +x aphelion
./aphelion --version

Step 2: Test with Your Database

# Generate 1,000 rows per table
./aphelion clone postgresql://user:pass@localhost/your_db \
  test_db --rows 1000 --seed 42

# Check the output
ls output/test_db/
# patients.sql, visits.sql, prescriptions.sql, etc.

Step 3: Compare Results

Verify that:

• All foreign keys are valid
• Unique constraints are satisfied
• Data quality matches your needs

Step 4: Replace Your Seed Script

Before (Faker.js):

# package.json
"scripts": {
  "seed": "node scripts/seed.js"
}

After (Aphelion):

# package.json
"scripts": {
  "seed": "aphelion clone $DATABASE_URL test_db --rows 1000 --auto-approve"
}

Step 5: Update CI/CD

GitHub Actions example:

# .github/workflows/test.yml
- name: Generate test data
  run: |
    curl -L https://algomimic.com/api/download/free -o aphelion
    chmod +x aphelion
    ./aphelion clone $DATABASE_URL test_db --rows 1000 --auto-approve
    
- name: Run tests
  run: npm test

Real-World Example: Healthcare Database

Let's see the difference for a realistic healthcare schema with 23 tables and 47 foreign keys.

Faker.js Approach

You would need to:

1. Manually define all 23 tables
2. Determine the correct insertion order (topological sort)
3. Track IDs for 47 foreign key relationships
4. Handle circular dependencies (e.g., patients ↔ providers)
5. Generate HIPAA-compliant fake data
6. Ensure unique constraints on SSNs, MRNs, etc.

Estimated effort: 40+ hours to write and debug

Aphelion Approach

aphelion clone postgresql://localhost/healthcare_prod \
  healthcare_test --rows 10000 --seed 42

# Output:
# 🔍 Introspecting schema...
#    ✓ Found 23 tables
#    ✓ Detected 47 foreign keys
#    ✓ Resolved 3 circular dependencies
#    ✓ Identified HIPAA-sensitive columns
#
# 📊 Generating data...
#    ✓ patients (10,000 rows)
#    ✓ visits (45,230 rows)
#    ✓ prescriptions (23,450 rows)
#    ✓ lab_results (67,890 rows)
#    ... (19 more tables)
#
# ✅ Generated 146,570 rows in 47 seconds
#    All constraints satisfied. Zero errors.

Estimated effort: 5 minutes

Frequently Asked Questions

Can I use Aphelion with Faker.js?

Yes! Many teams use both:

• Aphelion for database seeding (handles constraints)
• Faker.js for frontend mocks and unit test fixtures

They solve different problems and work well together.

Does Aphelion support custom data generators like Faker.js?

Yes! Aphelion has built-in generators for:

• Healthcare data (HIPAA-compliant)
• Financial data (PCI-DSS-safe)
• Telecom data (IMSI, IMEI, etc.)

You can also customize generators in the schema configuration file.

Is Aphelion free like Faker.js?

Aphelion is free forever for local development (up to 1,000 rows per table).

For production use, unlimited rows, and CI/CD automation, Pro is $49/year.

What if I'm not using PostgreSQL?

Currently, Aphelion only supports PostgreSQL. If you use MySQL, MongoDB, or other databases, stick with Faker.js or check out Tonic.ai.

We're planning MySQL support for Q1 2025.

How does Aphelion handle sensitive data?

Aphelion never copies real data. It:

• Introspects your schema structure only
• Generates 100% synthetic data from scratch
• Automatically detects PII columns (SSN, email, etc.)
• Replaces them with realistic but fake values

Conclusion: Choose the Right Tool

Faker.js is excellent for simple fake data, but it's not designed for database seeding. When you have foreign keys, unique constraints, or complex schemas, you need a tool that understands databases.

Aphelion is built specifically for PostgreSQL, with automatic constraint handling, foreign key resolution, and support for complex types.

Stop writing manual seed scripts. Let Aphelion handle the constraints automatically.