Data Generator for InterBase/Firebird is a utility designed to populate one or multiple InterBase/Firebird database tables with test data. It offers a wizard-based interface and a command-line tool to generate realistic, customizable datasets for development and testing. Users can define tables and fields, set value ranges, use masks for string fields, select values from lists or SQL queries, and configure generation parameters for each field type. The tool supports saving and editing data generation scripts, ensures referential integrity, and can disable triggers during data generation. It aims to simplify the process of simulating production-like environments for database testing and development.

Key Features

Unicode and Data Type Support Handles all InterBase/Firebird data types, including BIGINT and BOOLEAN, with Unicode compatibility.

• Supports domain-based types and various versions of InterBase/Firebird.
• Handles BLOB columns and complex data structures.

Customizable Data Generation Offers multiple modes for generating data, including random, incremental, list-based, and SQL query-based.

• Define value ranges, masks, and custom lists.
• Generate data into multiple fields simultaneously.

Script Management and Preview Allows saving and editing generated data as SQL scripts without immediate execution.

• Preview generated data before applying to the database.
• Save all generation parameters for reuse.

Referential Integrity and Triggers Maintains referential integrity for linked tables and can disable triggers during generation.

• Ensures valid test data for relational structures.
• Optionally empties tables before data generation.

Batch and Automation Tools Includes a command-line utility for template-based, automated data generation.

• Supports configuration files for repeatable tasks.
• Enables integration into CI/CD or automated test environments.

Benefits

Accelerates Development and Testing Reduces manual effort in creating test data, speeding up development cycles.

• Quickly simulates production environments.
• Enables comprehensive testing scenarios.

Ensures Data Quality and Consistency Provides tools to maintain data integrity and realistic test conditions.

• Automatic referential checks.
• Customizable NULL value settings and data distributions.

Flexible and Reusable Workflows Supports saving configurations and scripts for repeated use.

• Facilitates collaboration and consistency across teams.
• Simplifies maintenance of test data sets