What is an SQL Data Generator?
An SQL Data Generator creates synthetic sample rows and SQL INSERT (or UPSERT/COPY) scripts from a table schema without connecting to a database.
SQL Data Generator Online
Generate synthetic SQL seed data and INSERT scripts locally with schema-aware faker rules.
Local only • Synthetic fake data • No database connection • Seeded generation
Schema & generation options
Import CREATE TABLE SQL
Import CSV headers
| Include | Column | SQL type | Generator | PK | Null | |
|---|---|---|---|---|---|---|
SQL / preview / audit
Ready
How to Use
- Load a preset or define columns manually (name, SQL type, generator).
- Optionally paste CREATE TABLE SQL and import the schema.
- Choose SQL dialect, output mode, row count, seed, and locale.
- Click Generate SQL Data.
- Preview SQL or generated rows, then download SQL, CSV, or JSON.
Frequently Asked Questions
Does this tool connect to my database?
No. It never connects to or executes SQL against a database. Generation is static text output only.
Does it execute SQL?
No. You download or copy generated SQL and run it yourself in your own environment.
Is my schema uploaded to a server?
No. Schema editing, row generation, and SQL export run in your browser.
Is the generated data real personal information?
No. Values are synthetic fake data produced by seeded faker rules. They must not be treated as real identities.
Can I import an existing CREATE TABLE script?
Yes. Paste CREATE TABLE SQL and click Import schema to populate columns and types.
Can I customize column generators?
Yes. Each column supports generator types such as email, UUID, names, numbers, dates, enums, and sequences.
Can it suggest generator types from column names?
Yes. Column names like email, phone, created_at, and salary map to sensible default generator types.
Which SQL dialects are supported?
PostgreSQL, MySQL, MariaDB, SQLite, SQL Server, Oracle, and ANSI-style output with dialect-specific CREATE TABLE and INSERT formatting.
Which output modes are available?
Multi-row INSERT, single-row INSERT, MySQL REPLACE, MySQL/MariaDB UPSERT, PostgreSQL UPSERT, SQL Server MERGE, and PostgreSQL COPY.
Can I export CSV or JSON?
Yes. Download generated rows as CSV or JSON in addition to SQL.
Can I set a random seed?
Yes. Use a numeric seed for reproducible datasets across runs with the same schema and options.
Does it support NULL values?
Yes. Nullable columns can emit NULL based on generator null probability settings.
Can it generate UUIDs?
Yes. Use the uuid generator type for UUID/GUID-style text columns.
Can I generate primary keys automatically?
Yes. Mark a column as PK and use integer/uuid/sequence generators. You can also enable a synthetic primary key in advanced options if needed.
What is the maximum row count?
Up to 10,000 rows in-browser. Larger datasets may slow the browser; use smaller batches for interactive work.
Can it generate millions of rows?
Not in the browser. This tool targets development seed sizes (tens to thousands of rows), not warehouse-scale bulk generation.
Can it generate related tables with foreign keys?
This version focuses on single-table generation. Multi-table relational seeding with FK integrity is planned as a later enhancement.
Does it work offline?
Yes. After the page loads, generation works offline because processing is client-side.
What browsers are supported?
Modern Chromium, Firefox, Safari, and Edge with Web Worker support.
Is this tool free?
Yes. No account or per-generation charge.
Can I open generated SQL in other tools?
Yes. Hand off output to the SQL Validator, Formatter, or Splitter tools.
How is this different from Text to SQL?
Text to SQL converts existing delimited data into INSERT scripts. SQL Data Generator creates new synthetic rows from schema rules.
How is this different from Mock JSON Generator?
Mock JSON Generator outputs JSON payloads. SQL Data Generator outputs dialect-aware SQL seed scripts plus CSV/JSON exports of rows.
Can I use presets?
Yes. Presets for users, products, employees, orders, and blog posts provide quick starter schemas.
Will the same seed produce the same data?
Yes for the same schema, options, and seed value under the same tool version.
Should I use this on production databases directly?
Always review generated SQL first. Test on staging and validate constraints before applying seed scripts to shared environments.
Does it validate generated SQL?
It runs lightweight validation checks (for example UPSERT conflict columns). Use the SQL Validator handoff for full syntax parsing.
Can students use this for SQL practice?
Yes. It is useful for creating practice datasets for SELECT, JOIN, and INSERT exercises without sharing real data.
Does it use external AI APIs?
No. Data generation uses local faker rules and deterministic templates—no LLM calls.
Can I control locale for names and addresses?
Yes. Choose faker locales such as English, English (India), German, French, or Japanese.
What keyboard workflow is recommended?
Load a preset or import DDL, tune columns, set row count and seed, then click Generate SQL Data.