With dbForge Data Generator, databases can be populated with large volumes of realistic test data while preserving domain-level data integrity. This ensures the overall accuracy, consistency, and completeness of the generated data, aligning with the specific constraints and rules defined within the database schema.
Populate primary key columns: For primary key columns, Data Generator can generate sequential IDs from 1 to n, where n=127 for tinyint, 32,767 for smallint, 2,147,483,647 for integer, and 9,223,372,036,854,775,807 for bigint. Additionally, many generators have the Set values to be unique option. When it is enabled, dbForge Data Generator makes sure that the values generated for the column are unique. It is also possible to set a value distribution mode for the generated values. If you select Random by timestamp, the generated IDs will be inconsequent and every generation thereafter will populate new random values. In case you select Random by seed, IDs will be generated based on the specified seed value and when repopulating the column, the sequence will be preserved.
Populate foreign key columns: Data Generator automatically assigns the Foreign Key Generator to the columns that have foreign key constraints and generates foreign key values for a child table column based on the values contained in the parent table column. If necessary you can switch the Foreign Key (Auto Assigned) Generator to the Foreign Key (Manually Assigned) Generator and select a parent column. This way, you can create a single-column foreign key.
Preserve domain integrity for DATE columns: With dbForge Data Generator, you can ensure the consistency of dates in your databases. For example, to maintain control over the dates that cannot be prior or after other dates in a database, you can use the Range settings such as Offset from column and Offset from now and provide the offset details. This way you can guarantee that the generated values for both columns are realistic, consistent, and interconnected.
Populate tables with check constraints: dbForge Data Generator supports most of the existing check constraints. When the tool automatically assigns generators to columns, it sets the generator parameters to take account of any check constraints defined on a database.
Populate tables with a circular reference: Data Generator smartly detects dependencies within a database. When the tool spots a circular reference within a table to be populated, it throws a warning, and data generation is not possible in this case. When detecting a circular dependency between two tables, Data Generator displays a warning message as well, however, it allows changing the generator from the Foreign Key Generator for any other valid one. For such cases, data generation is possible.