GenRocket delivers comprehensive synthetic test data solutions designed to meet the rigorous demands of enterprise-level software development and testing. It addresses the critical challenge of obtaining sufficient volumes and varieties of realistic, non-sensitive test data, which is often a bottleneck when relying on masked production data or manual creation. The platform ensures that test data accurately reflects the structure and relationships of applications and databases, maintaining referential integrity and consistency across complex, multi-application environments. The solution streamlines the entire test data lifecycle, from initial data model setup and design to dynamic deployment and ongoing management. It offers extensive automation for creating accurate data models, supporting multiple versions to align with application changes. Developers and testers benefit from a wide array of data generators, enabling the creation of highly specific data for unit, integration, load, and complex workflow testing, including unique, negative, and edge cases. GenRocket integrates seamlessly into existing test automation frameworks and CI/CD pipelines, delivering on-demand, real-time data to accelerate testing cycles and improve software quality. Furthermore, its secure hybrid cloud architecture ensures that no sensitive customer data is ever stored or processed in the cloud, enhancing data privacy and compliance.

Features & Benefits

• Accelerated Test Data Project Modeling
  • Offers 15 different methods to quickly and accurately build test data projects that reflect data relationships in applications or databases.
  • XTS (Extract Table Schema) for SQL databases
  • Import from Metadata Management tools (e.g., Ab.Initio, Alation, Collibra)
  • XSD (XML Schema Definitions) and DDL (Data Definition Language) support
  • Quick Pattern Domain, Scratchpad, and Pre-Built Templates
  • Support for CSV, YAML, JSON, Avro JSON Schema, Spark Schema, and Salesforce
• Referential Integrity & Data Consistency
  • Maintains referential integrity across parent/child/sibling relationships within and across databases, ensuring data validity. Guarantees data consistency across multiple applications and data sources, crucial for regression testing and complex workflows.
• Data Model Life Cycle Management
  • Intelligently detects and allows automated updates to data model changes in source SQL databases (G-Delta), ensuring test data remains current. Automatically adapts impacted data domains, attributes, scenarios, and test data cases upon approval (G-Refactor). Supports managing multiple versions of data models and sources.
• Automated & Accelerated Test Data Design
  • Automates the design of commonly used test data (Unit, Integration, Load testing) and accelerates the creation of essential test data (unique, negative, edge case, permutation/combination data) using tools like G-Families.
• Self-Service Test Data Modification
  • Enables a central Test Data Engineering team to design test data, while developers and testers can modify test data cases via a self-service portal (G-Questionnaire) to meet exact test case requirements.
• Extensive Data Generators
  • Provides over 730 data generators to meet diverse data variety requirements, offering precise control over generated data characteristics.
  • Configurable parameters for random, patterned/sequential, null, or percentage-weighted data.
  • Exact length and type control for database compatibility.
  • Dynamic generation based on variables and complex logic.
  • Support for all valid permutations and combinations.
  • Consistent data generation for repeatable tests via "seed" feature.
  • Capabilities for data augmentation into existing datasets and stateful generation.
  • Intelligent linking and communication between generators for valid, related data.
  • Reusable assets and query generators for blending synthetic and real data.
  • Generation of transactional and historical data for past, present, or future scenarios.
• Test Data Case, Story & Epic Management
  • Enables the design and organization of test data for numerous testing scenarios, allowing orchestration of sequences of test data scenarios as part of larger testing processes or end-to-end workflows.
• Codeless Test Data Rules
  • Allows creation of simple or complex rules to control test data generation without coding, ensuring data meets very specific values and conditions. Rules can be created once and reused across multiple test data cases.
• Test Data Queries
  • Facilitates querying and blending of real production data values (e.g., account numbers, member IDs) with synthetically generated data for data validity, utilizing 17 query generators.
• Complex End-to-End Workflow Testing
  • Designed to handle complex decision-trees and map/track key-value pairs across heterogeneous environments, enabling the design and orchestration of test data delivery for multi-system workflows (e.g., G-Map Server, G-Workflow).
• Data Stubbing
  • Provides the ability to "stub" or mock responses from external systems within complex workflows when external dependencies are unavailable, expensive, or for black-box testing.
• Extensive Data Formats & Database Support
  • Supports 102+ data Receivers for a wide range of data formats and databases, ensuring compatibility across diverse enterprise environments.
  • Direct insertion into SQL and NoSQL databases without coding.
  • Real-time data delivery over REST APIs and SOAP.
  • Simulation of complex data feeds with nesting and calculations.
  • Support for message formats like Kafka, MQ, and SWIFT.
  • Generation of flat and nested XML and JSON files.
  • Data generation onto PDF forms (e.g., bank checks, medical forms).
  • Support for image formats (JPEG, GIF, PNG, TIFF, TIF).
  • Accurate generation of X12 EDI transactions (e.g., HIPAA-mandated formats).
• Self-Service Test Data Portal (G-Portal)
  • Provides a portal for large teams of developers and testers to search for and request test data, with categorization and tagging of Test Data Projects and an integrated ticketing system. (Currently in development/beta).
• Automated Test Data Repository (G-Repository)
  • Offers a central, automated repository for all test data and configuration files, automating the distribution and maintenance of fresh, accurate test data across global teams in on-premise and private cloud environments.
• Comprehensive Test Environment Integration
  • Integrates exact volume and variety of test data into test automation frameworks and CI/CD pipelines (AWS, Azure, GCP), and testing tools (e.g., Selenium, JMeter, Tricentis TOSCA). Supports containerization (Docker) and Maven Repositories for deployment.
  • Integration with in-house test automation frameworks.
  • Simultaneous data generation into multiple test environments.
  • Fast data generation (millions to billions of rows in minutes).
  • Support for multiple users requesting and running scenarios simultaneously (GMUS).
  • Ability to read and process API responses in test environments.
  • Data logging feature for regulatory compliance.
• Dynamic Data Generation via API
  • Enables real-time dynamic data generation via a powerful, well-documented API, supporting "electronic testers" for automated decisions and on-the-fly test data creation.
• Production Data Subsetting & Masking (G-Migration+)
  • Offers high-speed data subsetting from select SQL databases with referential integrity. Masks sensitive data using "Synthetic Data Replacement," where sensitive data is synthetically generated while non-sensitive production data is migrated, ensuring security without storing customer data.
• Management & Access Controls
  • Provides extensive security control through Team Permissions, ensuring granular access controls and permissions across teams and projects.
• Reporting (G-Analytics)
  • Offers a comprehensive reporting and analytics dashboard (G-Analytics) for visibility into user activity and data generation activity within the platform.
• Secure Architecture
  • Features a secure hybrid cloud architecture where no customer data is ever stored or processed in the cloud, with all data generated on-premise or in a private cloud. Supports Single Sign On (SSO) and Multi-Factor Authentication (MFA) for enhanced enterprise security.