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Mock Data Generator
Define columns and types, generate realistic fake data as SQL INSERT statements, CSV, or JSON.
Columns
Output
CREATE TABLE users ( id SERIAL PRIMARY KEY, name TEXT, email TEXT, active BOOLEAN, created_at TIMESTAMPTZ ); INSERT INTO users (id, name, email, active, created_at) VALUES (1, 'Hank Gonzalez', '[email protected]', FALSE, '2023-04-09T01:20:00Z'); INSERT INTO users (id, name, email, active, created_at) VALUES (2, 'Ivy Johnson', '[email protected]', TRUE, '2020-12-14T03:19:00Z'); INSERT INTO users (id, name, email, active, created_at) VALUES (3, 'Grace Rodriguez', '[email protected]', FALSE, '2022-06-10T13:48:00Z'); INSERT INTO users (id, name, email, active, created_at) VALUES (4, 'Mia Gonzalez', '[email protected]', FALSE, '2021-01-21T21:56:00Z'); INSERT INTO users (id, name, email, active, created_at) VALUES (5, 'Charlie Hernandez', '[email protected]', FALSE, '2022-08-24T07:34:00Z'); INSERT INTO users (id, name, email, active, created_at) VALUES (6, 'Hank Wilson', '[email protected]', FALSE, '2020-11-06T17:41:00Z'); INSERT INTO users (id, name, email, active, created_at) VALUES (7, 'Eve Smith', '[email protected]', TRUE, '2020-11-22T06:23:00Z'); INSERT INTO users (id, name, email, active, created_at) VALUES (8, 'Sam Smith', '[email protected]', TRUE, '2020-09-07T21:45:00Z'); INSERT INTO users (id, name, email, active, created_at) VALUES (9, 'Sam Anderson', '[email protected]', TRUE, '2020-11-08T22:23:00Z'); INSERT INTO users (id, name, email, active, created_at) VALUES (10, 'Alice Rodriguez', '[email protected]', FALSE, '2021-08-03T16:37:00Z');
Database Access
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