Features

Every tool your data team needs

From blank schema to production-ready synthetic dataset. Generate, extend, and redact — all in one platform.

dashboard.hadarac.com
Generate Dataset Ready

Generate 500 rows of e-commerce transaction data with user_id, product_name, price, category, and purchase_date

user_idproduct_namepricecategorypurchase_date
USR-1042Wireless Headphones$149.99Electronics2024-03-12
USR-0387Running Shoes$89.50Sports2024-03-13
USR-2891Coffee Maker$74.00Home2024-03-13
USR-0124Yoga Mat$34.99Fitness2024-03-14
USR-3374Desk Lamp$45.00Office2024-03-14
USR-0756Protein Powder$59.99Nutrition2024-03-15
494 more rows • 500 total
Generate
Generate highest quality synthetic
datasets with simple instructions
Extend
Adjust and extend your
own datasets with ease
Redact
Redact sensitive data
on demand
SOC 2GDPRAES-256
Security
End-to-end encryption and
secure storage
InputGenerateValidateExportDone
Workflows
Build re-usable data
generation workflows
Quality Rating
Full control over generated data with
our data quality rating system
Generate

Describe your dataset. Get it instantly.

Write a plain-English description of what you need — columns, domain, volume, edge cases. Hadarac generates a complete, realistic dataset in under two seconds. No schema files. No sample data. No SQL.

Start generating free →
hadarac.com/generate
Prompt
Generate 200 realistic e-commerce transactions for a UK fashion retailer. Include order_id, customer_name, email, product, quantity, price_gbp, and status.
200 rows·7 columns·CSV · Parquet
Output200 rows generated
order_idnameemailproductqtypricestatus
#UK-8821Isla T.isla@…Linen blazer1£89.99shipped
#UK-8822Marcus P.m.patel@…Cord trousers2£112.00processing
#UK-8823Fiona H.fionahm@…Silk scarf1£34.50delivered
#UK-8824Aiden R.aiden@…Wool coat1£249.00shipped
Redact

Replace PII before it ever leaves your stack.

Upload any CSV containing real customer data. Hadarac detects and replaces names, emails, phone numbers, postcodes, and dates of birth with statistically realistic synthetic equivalents — preserving format, distribution, and referential integrity.

See how redaction works →
hadarac.com/redact
Input file

customers_prod.csv

1,204 rows · 9 columns · 84 KB

PII detected
Before → After
full_nameJonathan Ashworth-ClarkeMarcus Pemberton
emailj.ashworth@clarkeltd.co.ukm.pemberton@synth.data
phone+44 7700 900461+44 7000 000127
postcodeEC1A 1BBSW1A 9ZZ
dob1987-03-141985-07-22
1,204 / 1,204 rows redacted
Extend

Add columns to any dataset without starting over.

Have a dataset but need more signal? Upload your CSV or Parquet and tell Hadarac which columns to add. It infers relationships from existing data and generates new columns that are statistically consistent with what you already have.

Try Extend →
hadarac.com/extend
Existing columns
user_idnamecityagesignup_date
Add new columns
annual_income, job_title, credit_score
Result+3 columns added
namecityageincome ✦job_title ✦credit ✦
Alice B.London29£54,200Product Mgr761
Tom K.Berlin34€71,800ML Engineer810
Priya S.NYC27$83,500Data Analyst688
Sam W.Sydney42A$92,000Sr Dev742

Everything included

What you get

Every feature available from day one. No gated modules, no hidden add-ons.

Natural-language dataset generation
Schema inference from examples
PII redaction with realistic replacements
Column extension without re-generation
CSV and Parquet export
JSON output support
REST API with full CRUD access
Python SDK (pip install hadarac)
Prompt history and versioning
Feedback-driven data refinement
Star-rating quality scoring
Concurrent job queue
Team sharing & credit pooling
Custom SSO (SAML 2.0)
End-to-end encryption (TLS 1.3)
Zero-retention processing
EU and US region selection
GDPR & CCPA compliance toolkit
Webhook notifications on job complete
Audit log export

Integrations

Works with your stack

Export to any format, integrate with any pipeline. Hadarac fits into the tools you already use.

CSV Export
Parquet Export
JSON Export
PostgreSQL Database
BigQuery Warehouse
Snowflake Warehouse
dbt Transform
Apache Spark Processing
Python SDK API
REST API API
pandas Library
S3 / GCS Storage
Airbyte Ingestion
Fivetran Ingestion
YAML Schema Config

Don't see your tool? Request an integration →

How we compare

Hadarac vs Faker.js vs Mockaroo

All tools generate fake data — but they're built for very different jobs.

Feature Hadarac Faker.js Mockaroo
Plain English prompt input
Contextually coherent rows
PII redaction (GDPR-ready)
Extend existing datasets
Parquet / CSV / JSON export
No-code UI (no setup)
Programmatic API
Local / offline use
Free tier available

Faker.js is great for seeding unit tests. Mockaroo for simple CSV mocks. Hadarac is for teams who need coherent, schema-aware, privacy-safe data at scale.

Live demo

See it work in real time

No account needed. Pick a schema, hit Generate, and watch 10 rows of realistic synthetic data appear — instantly.

Try it live

No account needed. 10 rows, instant results.

Schema:order_idproduct_namecategoryquantitypricecountrystatus· 10 rows

Ready to generate

order_id · product_name · category · quantity · price · country · status

Ready to start generating?

Free tier available. No credit card required. Up and running in under 2 minutes.