SQL to Mock Data Generator

Generate realistic mock data from SQL table schemas

0.5; case 'date': const date = new Date(2024, 0, 1); date.setDate(date.getDate() + index); return date.toISOString().split('T')[0]; case 'datetime': const dt = new Date(2024, 0, 1, 10, 0, 0); dt.setHours(dt.getHours() + index); return dt.toISOString().replace('T', ' ').split('.')[0]; case 'string': default: return `Sample ${columnName} ${index + 1}`; } }, getOutput() { if (!this.mockData.rows) return ''; if (this.outputFormat === 'sql') { return this.generateSQL(); } else if (this.outputFormat === 'json') { return JSON.stringify(this.mockData.rows, null, 2); } else { return this.generateCSV(); } }, generateSQL() { let sql = ''; const tableName = this.mockData.tableName; const columns = this.mockData.columns.map(c => c.name); for (const row of this.mockData.rows) { const values = columns.map(col => { const value = row[col]; if (typeof value === 'string') { return `'${value.replace(/'/g, \"''\")}'`; } else if (typeof value === 'boolean') { return value ? '1' : '0'; } else if (value === null || value === undefined) { return 'NULL'; } return value; }); sql += `INSERT INTO ${tableName} (${columns.join(', ')}) VALUES (${values.join(', ')});\\n`; } return sql; }, generateCSV() { const columns = this.mockData.columns.map(c => c.name); let csv = columns.join(',') + '\\n'; for (const row of this.mockData.rows) { const values = columns.map(col => { const value = row[col]; if (typeof value === 'string' && (value.includes(',') || value.includes('\"'))) { return `\"${value.replace(/\"/g, '\"\"')}\"`; } return value; }); csv += values.join(',') + '\\n'; } return csv; }, loadExample() { this.sql = `CREATE TABLE users ( id INT PRIMARY KEY AUTO_INCREMENT, firstname VARCHAR(50), lastname VARCHAR(50), email VARCHAR(100), age INT, status VARCHAR(20), created_at DATETIME );`; this.generate(); }, copyOutput() { navigator.clipboard.writeText(this.getOutput()); } }">

Error

Features

  • Parse SQL CREATE TABLE statements
  • Generate realistic mock data based on column names and types
  • Support for common data types (INT, VARCHAR, DATE, etc.)
  • Output as SQL INSERT, JSON, or CSV
  • Smart field detection (email, phone, name, etc.)
  • ⚠️ Client-side processing - your schemas never leave your browser