dbForge Data Generator

dbForge Data Generator for SQL Server is a powerful GUI tool for a fast generation of meaningful test data for databases. dbForge dummy data generation tool includes 200+ predefined data generators with sensible configuration options, that allow to emulate column-intelligent random data. The tool also allows generating demo data for databases already filled with data and create your own custom test data generators. dbForge Data Generator for SQL Server can save your time and effort spent on demo data generation by populating SQL Server tables with millions of rows of sample data that looks just like real data

Key Features:

• Full support for all column data types: The tool supports a massive range of column data types
  
• Multiple generators with data customisation: Data Generator comes with individual generators for each supported data type, that allow to customise
  
• SQL data integrity support: The tool supports foreign keys for generation of consistent data across multiple tables. It also allows disabling triggers and constraints to avoid interference with database logic.
  
• Domain integrity support: The tool supports check constraint for generation of consistent data across a single column or multiple columns of a table. It also allows disabling check constraints to avoid interference with database logic.
  
• Multiple ways to populate data: The generated data population script that can immediately be executed against a SQL Server database, saved for future use or edited in the internal editor.
  
• Basic generators: With the collection of 15+ basic generators, you can populate tables with various types of values.
  
• Meaningful generators: dbForge Data Generator for SQL Server includes 190+ meaningful generators that allow to populate tables with realistic test data.
  
• User-defined generators: You can create, save and use your own generators that would better meet your needs, instead of customising existing generators over and over again.
  
• Command-line interface: With the command-line functionality, you can save time by scheduling routine data generation tasks.