![]() GenRocket offers the most test data formats in the industry Production data has many gaps and does not meet all test case requirements. Volume is limited to what is available in the synthesized production database copy. ![]() Volume is limited to what is available in the production database. Generate any volume of data in seconds to minutes, on demand, as needed by each test case Generate any variety of new and unique data based on specific rules & conditions regardless of what is in the production databaseĭata variety is limited to what is in your masked production data subsetĭata variety is limited to what is in your synthesized production data subset The price range for many of the new synthetic TDM platforms where some license fees increase with data volume The price range for traditional TDM systems where some license fees increase with data volume The price range for the GenRocket synthetic TDA platform with unlimited data volume The table below contains the most important aspects of TDM and describes how each category of test data management platforms address them. Let’s compare the way GenRocket’s Synthetic Test Data Automation Compares with Traditional TDM and Synthetic TDM. How GenRocket Compares with Traditional and Synthetic TDM However, both approaches still have the same limitations in data volume, variety and conditions that are evident in masked production data from traditional TDM systems.īoth traditional TDM and synthetic TDM tools also require dedicated infrastructure for hosting and data storage where GenRocket only requires a small, light-weight Java Runtime and Repository to run and store Test Data Case instruction sets. Both approaches are alternatives to the traditional TDM data masking process while still eliminating the use of sensitive data (PII or PHI). Some of these tools produce a statistically equivalent replica of the entire database using synthetic data. These platforms use machine learning to examine a production database and use synthetic data generation as a data masking technique. Synthetic TDM (e.g., Tonic, Hazy, Mostly AI)Ī recent evolution of the traditional TDM paradigm is the emergence of Synthetic TDM. This can be very costly in terms of time and resources. Testers must query the test database for the data they need or augment it with manually created data. While test data provisioned in this manner is realistic, it’s not conditioned to meet the needs of a given test case. In traditional TDM, test data is often reserved by a tester for a given test and refreshed prior to its next use. It has formalized the process of copying and masking a subset of a production database to make it ready for testing. Traditional TDM is the familiar model for provisioning test data commonly in use today. Traditional TDM (e.g., IBM, Broadcom, Informatica) And TDA is affordably priced according to the number of data environments that are modeled, offering unlimited data generation for each data environment modeled by a Test Data Project. TDA allows data to be instantly provisioned by testers using a self-service platform in the volume and variety needed to achieve full test coverage. This instruction set is used to generate a fresh copy of synthetic data in real-time as automated tests are run in the CI/CD pipeline. Controlled and conditioned synthetic data is defined by a light-weight instruction set in an executable Test Data Case. It brings the ability to model and design any type of test data for any type of test based on pre-defined rules. Synthetic TDA is unlike any other form of TDM. Let’s clearly define each TDM category and compare the way each one addresses the most important elements of an enterprise-class test data solution. It also removes the limitations of other synthetic data platforms that produce a synthetic data replica of a production database to provision test data. This new and innovative approach automates and accelerates many cumbersome aspects of traditional TDM. GenRocket’s synthetic data platform creates a new category of Test Data Management (TDM) that we refer to as Synthetic Test Data Automation (TDA).
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