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Synthetic Data Generator — Fake, Test & Mock Data Generator

Generate realistic synthetic, fake, test, and mock data with correlated fields, built-in presets, custom schemas, deterministic seeding, and multiple output formats (JSON, CSV, NDJSON).

What does the Synthetic Data Generator do?

This actor is a synthetic data generator that produces fake data, test data, and mock data on demand -- no web scraping required. It produces structured datasets using Faker.js for realistic data generation and Copycat for deterministic, reproducible output. Use it to create test data, seed databases, populate staging environments, or benchmark data pipelines.

Key features

• Built-in presets -- One-click generation for user profiles, companies, e-commerce products, and server log events
• Custom schemas -- Define your own field names and types to generate exactly the data shape you need
• Cross-field correlations -- Age tracks with salary, company size correlates with revenue, out-of-stock items have zero quantity
• Deterministic mode -- Set a random seed for identical output across runs (same seed + same config = same data every time)
• Multiple output formats -- JSON (Apify dataset), CSV, or NDJSON
• 16 locales -- Generate names, addresses, and phone numbers in English, German, French, Japanese, Chinese, and more
• Fast and cheap -- No proxy, no browser, no external API calls. Generates 10,000+ records per second on 256MB memory

Built-in presets

Custom schema

Define any combination of fields with the customSchema input (JSON array):

[
{"name":"user_id","type":"uuid"},
{"name":"username","type":"name"},
{"name":"signup_date","type":"datetime"},
{"name":"plan","type":"enum","options":{"values":["free","pro","enterprise"],"weights":[0.7,0.2,0.1]}},
{"name":"monthly_spend","type":"number","options":{"min":0,"max":500}}
]

Supported field types

string, integer, number, boolean, date, datetime, email, phone, address, name, first_name, last_name, company, url, uuid, city, state, zip, country, job_title, salary, sentence, paragraph, enum

For enum type, pass options.values (array of choices) and optionally options.weights (probability weights).

Input

Output

JSON format (default)

Records are pushed to the Apify dataset. Each record is a flat JSON object matching the selected preset or custom schema.

CSV / NDJSON format

The file is saved to the key-value store under the key OUTPUT. A summary record is also pushed to the dataset with download instructions.

Example output (user_profiles preset)

{
"id":"a1abcd86-4c43-4300-864f-066b9f5e43eb",
"first_name":"Lydia",
"last_name":"MacGyver",
"email":"Taryn8@gmail.com",
"phone":"(444) 909-7300",
"date_of_birth":"2005-01-20",
"age":21,
"gender":"Female",
"address":"8239 Johnston Shore",
"city":"West Chanelleburgh",
"state":"Utah",
"zip":"00084",
"country":"Holy See (Vatican City State)",
"job_title":"Principal Applications Developer",
"company":"Nienow-Gibson, Bruen and Mayer",
"salary":109866,
"created_at":"2025-09-23T21:04:26.698Z"
}

Cost

This actor uses Pay Per Event pricing:

• $0.10 per actor start
• $0.0001 per data record generated

Example: Generating 10,000 user profiles costs $0.10 (start) + $1.00 (records) = $1.10 total.

Performance

Use cases

• Database seeding -- Populate development and staging databases with realistic test data
• API testing -- Generate request/response payloads for load testing and integration tests
• Data pipeline validation -- Feed synthetic data through ETL pipelines to verify transformations
• UI prototyping -- Fill dashboards and reports with realistic-looking data
• Machine learning -- Generate training data for models that need structured tabular input
• Demo environments -- Create convincing demo data without using real customer information

FAQ

How do I generate fake data for testing?

Pick a preset (user profiles, companies, e-commerce products, or log events) or define a customSchema, set recordCount, and run. The actor returns fake test data in JSON, CSV, or NDJSON with no web scraping involved.

Can this generate mock data as a CSV or API output?

Yes. Set outputFormat to csv or ndjson to get a downloadable file from the key-value store, or keep json to read records straight from the Apify dataset via the API.

How do I produce reproducible synthetic data every run?

Set a non-zero seed. The same seed plus the same config yields identical output on every run, so your test data and mock datasets stay stable across CI runs.

Need more features?

If you need additional field types, presets, or output formats, file an issue or get in touch. We actively maintain this actor and welcome feature requests.