Features
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Key features
How does it work? |
| Walk-through |
| Introductory walk-through |
Detection of metadata changes
When you refresh the tables (Project | Refresh tables) in an opened project or when you re-open an existing data generator project, DB Data Generator automatically reads the database and detects when a column or table has changed or has been deleted. It will then automatically apply this change to the table(s) in the project.
Cross-platform support
Direct access (native drivers) to Oracle, MS SQL Server, MS Access, MySQL, PostgreSQL, InterBase and Firebird.
Generation of data for multiple tables
You can select the tables you wish to fill with test data. A DB Data Generator project can hold one or hundreds of tables.
Generation of data that matches to your database schema
DB Data Generator reads the database schema details from your database. This schema information (metadata) is used for generating syntactically correct data that automatically matches your domain values (data types).
More than thirteen built-in standard generators
DB Data Generator includes multiple built-in standard data generators (fill methods) for generating different kinds of data. For example, the integer data generator generates random integer values, the string generator generates random strings. You can also use sequences for numeric fields.
Conversion of source data
Source data that is from a different data type, will be converted automatically.
Single-click test data generation
When you have connected to a database, DB Data Generator automatically chooses the most appropriate data generation settings for each field. Ofcourse you can fine-tune these settings but you can also choose to generate data with this default settings. All you have to do then, is clicking the "Generate data" button.
Default field settings
When a table is added to a Data Generator project, DB Data Generator will automatically determine the best data generation settings (fill method) for the fields in the table. The field settings depend on the data type, relationship to other tables (foreign key), not null setting and other table or column constraints.
Validation of data generation settings
DB Data Generator will check your table settings and field settings before test data is being generated. It will check for wrongly entered values and it will check if a field setting is valid based on the other settings (such as for example the number of rows to generate). It is for example possible that you've selected a fill method "Random value from data table" for a field with a unique constraint. If the number of records (lines) in the data table is not enough to generate unique values for the specified number of rows to generate, DB Data Generator will raise an error.
Generation of data from an extensive set of included CSV files (data tables)
When you install DB Data Generator, a number of CSV files (delimited text files) with thousands of names, zip codes, cities, countries, and more, will be installed.
Project-oriented architecture
DB Data Generator is project-oriented, so a user can create a project that indicates which database and which tables to fill and how to generate the test data. Projects can be as simple as loading a single table, or as complex as loading hundreds of tables.
Generates data based on user-defined masks
A powerful way to generate meaningful data that matches your needs is to fill a field using the "Random text using mask" generator. By using the "Random text using mask" fill type, you can generate strings that match a defined pattern. You can use the "random text using mask" generator with any data column that has a data type that accepts a string (char, varchar, clob, string, text, etc...) and user-defined types (domains) based on these string types.
Randomly generated values can be constrained to a range of values
DB Data Generator allows you to place restrictions on data values it will generate. For example, integers can be constrained to a range of values. Date/time values can be constrained to a date range. Text strings can be constrained to a fixed set of choices (also known as enumerations).
Output generated data to the database or to a SQL insert script
When you start generating the data, you can choose to output to the database or to a SQL file with insert statements.
Option to clear the contents of the tables before inserting new data
When you have checked the "Empty table" setting for a table, you are prompted to clear the contents of the table before inserting rows. DB Data Generator then attempts to delete the existing data in the table before generating the new data.
Maintains referential integrity, with support for foreign keys
DB Data Generator automatically controls referential integrity for linked tables. When data is inserted, it will be done in correct order. When a child column is part of a relationship it will by default load random data from the parent column in the parent table. DB Data Generator also correctly handles multi-column foreign key constraints.
Optionally disable triggers
You can disable triggers to avoid potential problems when inserting data.
Pre-data generation and post-data generation scripts
You might have a script that you want to run before or after the generation of test data. You can specify such scripts DB Data Generator's project settings dialog.
Supports percentage of null values setting
Supports direct access to Oracle, MS SQL Server, MS Access, MySQL, PostgreSQL, InterBase and Firebird
Generation of data from randomly chosen records from another database table
You can populate a table, or multiple columns in a table, by linking to another table in your database.
Import your own CSV files (delimited text files) to use for data generation
Developers can create new data tables (delimited text files) so that they can be used inside the DB Data Generator environment.
