Compare IRI RowGen vs. TestBench for IBM i

IRI RowGen generates rows ... billions of rows of safe, intelligent test data in database, flat-file, and formatted report targets ... using metadata, not data. RowGen synthesizes and populates accurate, relational test data with the same characteristics of production data. RowGen uses the metadata you already have (or create on the fly) to randomly generate structurally and referentially correct test data, and/or randomly select data from real sets. RowGen lets you customize data formats, volumes, ranges, distributions, and other properties on the fly or with re-usable rules that support major goals like application testing and subsetting. RowGen uses the IRI CoSort engine to deliver the fastest generation, transformation, and bulk-load movement of big test data on the market. RowGen was designed by data modeling, integration, and processing experts to save time and energy in the creation of perfect, compliant test sets in production and custom formats. With RowGen, you can produce and provision safe, smart, synthetic test data for: DevOps, DB, DV, and DW prototypes, demonstrations, application stress-testing, and benchmarking -- all without needing production data.

Testing and managing test data for IBM i, IBM iSeries, and AS/400 systems requires thorough validation of complex applications, extending down to the underlying data. TestBench for IBM i offers a robust and reliable solution for test data management, verification, and unit testing, seamlessly integrating with other tools to ensure overall application quality. Instead of duplicating the entire live database, you can focus on the specific data that is essential for your testing needs. By selecting or sampling data while maintaining complete referential integrity, you can streamline the testing process. You can easily identify which fields require protection and employ various obfuscation techniques to safeguard your data effectively. Additionally, you can monitor every insert, update, and delete action, including the intermediate states of the data. Setting up automatic alerts for data failures through customizable rules can significantly reduce manual oversight. This approach eliminates the tedious save and restore processes and helps clarify any inconsistencies in test results that stem from inadequate initial data. While comparing outputs is a reliable way to validate test results, it often involves considerable effort and is susceptible to mistakes; however, this innovative solution can significantly reduce the time spent on testing, making the entire process more efficient. With TestBench, you can enhance your testing accuracy and save valuable resources.