Product Listings
Perforce Delphix is a software designed to provide data virtualization and management capabilities for enterprises. The software enables organizations to deliver secure and compliant copies of production data to development, test, and analytics environments. It streamlines the process of data provisioning, automates data delivery, and reduces storage requirements by creating virtual copies of databases. Perforce Delphix also offers features for data masking to help protect sensitive information and capabilities for data refresh and rewind, supporting agile development practices and faster application releases. The software addresses challenges related to slow data provisioning, data security, and compliance in complex IT environments.
Informatica Cloud Test Data Management (Legacy) is a software that enables organizations to create, manage, and provision secure and reliable test data in cloud environments. The software helps automate the generation and masking of test data, supporting compliance with privacy regulations and protecting sensitive information during application development and testing cycles. It addresses business challenges related to maintaining data quality, reducing risks associated with data exposure, and optimizing testing processes by providing realistic but sanitized datasets for quality assurance and development teams. The software integrates with various cloud and on-premises data sources, facilitating efficient data subsetting and management across enterprise systems.
IBM InfoSphere Optim Test Data Management is a software designed to help organizations manage and provision test data for application development, quality assurance, and testing environments. The software enables users to create realistic, subsetted, and masked versions of production data, facilitating compliance with data privacy regulations and reducing risks associated with sensitive information. InfoSphere Optim Test Data Management supports automation of test data extraction, data masking, and data provisioning activities, ensuring that development and testing teams have access to relevant and compliant datasets. By providing scalable data management capabilities, the software aims to streamline application lifecycle processes and optimize the efficiency of testing and development efforts.
Parasoft Virtualize is now AI-augmented, enabling faster, smarter service virtualization for development and testing teams. It simulates APIs, databases, mainframes, and other endpoints to eliminate delays caused by unavailable systems. With its agentic AI assistant, teams can generate virtual services using natural language—no scripting or service definition files required. AI-powered learning mode continuously updates simulations based on live traffic, while Change Advisor automates impact analysis and service updates. Virtualize supports over 120 protocols and message formats, and includes test data generation, masking, and integrated API testing. Its intuitive interface and reusable environments streamline CI/CD workflows, improve test coverage, and reduce manual effort—making continuous testing more efficient and scalable.
DATPROF simplifies getting the right test data in the right place at the right time. Masked, generated, subsetted and automated at the push of a button. Or integrated into your CI/CD pipeline. All from one central test data management platform.
Accelario is a software designed to streamline data management processes, focusing on test data automation and data migration capabilities for organizations. The software enables users to mask, provision, synchronize, and refresh datasets across environments while maintaining data privacy and compliance requirements. It supports the acceleration of database cloning and copying, reducing time and manual effort associated with preparing data for development, testing, and analytics purposes. Accelario’s features include automated testing environment preparation, data version control, and integration with popular database platforms to solve business challenges related to efficient and secure data handling in application lifecycle management.
Tonic.ai frees developers to build with safe, high-fidelity synthetic data to accelerate software and AI innovation while protecting data privacy. Our platform delivers enterprise-grade solutions for generating, de-identifying, and managing realistic data at scale. Generate synthetic data from scratch to drive greenfield product development with Tonic Fabricate. De-identify sensitive production data for secure, effective use in testing and QA with Tonic Structural. Avoid collisions in testing with isolated data environments spun up on-demand through Tonic Ephemeral. Redact and synthesize sensitive entities in unstructured data to safely fuel AI initiatives with Tonic Textual. Unblock innovation, eliminate collisions in testing, accelerate your engineering velocity, and ship better products, all while safeguarding data privacy with Tonic.ai.
Bitwise Test Data Management is a software designed to facilitate the generation, management, and provisioning of test data for application development and quality assurance processes. The software provides functionalities such as data masking, data subsetting, and synthetic data creation to ensure compliance with data privacy requirements while enabling robust testing environments. It helps organizations address challenges related to securing sensitive data, maintaining realistic testing conditions, and reducing data provisioning cycle times. The software supports integration with various database systems, automates data operations, and enables repeatable test scenarios to improve efficiency in testing and development workflows.
Mage Platform is a software designed for building, training, and deploying machine learning models. It provides automated workflows for data preprocessing, feature engineering, and model selection, aiming to streamline the machine learning pipeline for data scientists and engineers. The software supports integration with various data sources and tools, enabling users to manage experiments, monitor model performance, and handle model deployment in production environments. Mage Platform addresses the challenge of operationalizing machine learning projects by offering a collaborative environment and reducing the complexity of managing resources throughout the model lifecycle.
Bringing together a host of traditional and modern powerful test data management capabilities, Redgate Test Data Manager allows users to:
*Find sensitive data in databases, and obfuscate it with realistic looking data, through automated discovery and deterministic masking.
*Provision a slice of data in the exact size required, with referential integrity intact with subsetting.
*Self-serve small, lightweight clones through data virtualization. With ephemeral servers, each clone is a perfect copy, including database, database version, and operating system.
*Integrate quality test data into existing CI/CD pipelines with the command line interface.
*Simple visibility and management with the graphical user interface.
Solix Common Data Platform (CDP) is an enterprise software designed to manage, store, and analyze structured and unstructured data across various sources. The software provides features such as data archiving, privacy management, and analytics to support governance, compliance, and business intelligence initiatives. It enables organizations to consolidate data silos, simplify data lifecycle management, and ensure accessible data for business operations and reporting. Solix Common Data Platform supports regulatory compliance by providing tools for retention, security, and oversight of sensitive information. The software addresses challenges related to optimizing storage costs, streamlining access, and enabling data-driven decision making across business units.
icaria TDM facilitates the integration of test data management within CI/CD pipelines by automating the supply of test data. It identifies and retrieves the necessary input data for specific test cases, delivers it on-demand, and provides expected results for comparison with actual outcomes. These functions are accessible via REST services.
The system’s data profiling capabilities determine the appropriate data archetypes for specific test cases. It locates these archetype instances across various application repositories. Through data subsetting, icaria TDM copies, masks, and stores these data instances in internal repositories. These repositories are linked to specific test cases, allowing for repeated use as required.
Additionally, icaria TDM monitors and identifies inconsistencies in data models and parameterization across environments. It adjusts these discrepancies when necessary, aiding in the optimization of DevOps processes.
K2view Data Product Platform gets enterprise data AI ready: protected, complete, and accessible in a split second. It packages data as reusable products for use cases like Test Data Management, Data Masking, Synthetic Data Generation, and Generative AI. The platform connects to any data source and provisions data to any environment, automatically discovering, unifying, transforming, and masking sensitive information while preserving referential integrity across systems. Built for enterprises on patented Micro-Database technology, it organizes data by business entity, for example customer, order, and product, to ensure real time synchronization, in flight cleansing, and secure delivery. AI assisted copilots let users perform complex data operations through natural language chatbots. Using AI and machine learning, K2view creates compliant synthetic data for testing and model training, helping enterprises accelerate agility, improve data quality, and ensure regulatory compliance.
Amazon SageMaker is a software that enables developers and data scientists to build, train, and deploy machine learning models at scale. The software offers a managed environment that supports various machine learning frameworks and algorithms, including built-in tools for data labeling, model tuning, and data preparation. It provides infrastructure automation for distributed training, as well as model hosting for real-time and batch inference. Users can take advantage of integrated Jupyter notebooks to perform data exploration and preprocessing. Amazon SageMaker supports deployment across cloud and edge environments, helping organizations accelerate and standardize machine learning workflows. The software addresses the challenges of operationalizing machine learning by streamlining development and deployment processes.
Enov8 Test Data Management is a software designed to support the creation, management, and provisioning of test data across development and testing environments. The software provides capabilities for data discovery, masking, and synthetic data generation, allowing organizations to maintain data privacy and compliance with regulatory requirements. It facilitates data reusability and enables teams to efficiently refresh and allocate test data, helping to reduce project delays linked to data bottlenecks. Enov8 Test Data Management addresses challenges related to test data compliance, data availability, and environment stability by offering centralized control and automation features for managing test data throughout software delivery lifecycles.
Test Data Manager is a software designed to assist organizations in managing test data for quality assurance and software development processes. The software provides features for creating, masking, and provisioning test data, enabling teams to generate compliant and relevant data sets. It helps streamline testing workflows by automating data creation and ensuring sensitive information is protected through data masking. Test Data Manager addresses business challenges related to test data availability, compliance with data privacy regulations, and the efficiency of test cycles. The software supports integration with various testing frameworks and environments to facilitate end-to-end testing and improve overall application reliability.
Avo iTDM is a software designed to support test data management in automated testing environments. It enables the creation, management, and provisioning of test data required for software testing processes, facilitating compliance with data privacy regulations and organizational policies. The software allows users to generate synthetic data, mask sensitive information, and reuse data sets to ensure accurate and repeatable test scenarios. Its features aim to solve the business problem of providing consistent and secure test data, reducing manual intervention and improving testing efficiency while minimizing risks related to data privacy and compliance.
Curiosity Software focuses on alleviating challenges related to test data management for enterprises, with the help of artificial intelligence. Their prime mission revolves around assisting organisations in handling issues associated with complexity, legacy, scalability, and regulatory compliance of their data. The company has years of experience in improving enterprise data delivery, providing a unique approach towards managing data. Curiosity Software targets primary obstacles to productivity including test data discovery, delivery, compliance, and quality. Their Enterprise Test Data platform aims to assist teams by easing their intricate application landscape and ensuring certainty and clarity throughout the data journey.
ExactData is a software designed to facilitate high-performance data management, analysis, and modeling for scientific and engineering applications. The software provides tools for handling complex datasets, including capabilities for advanced data visualization, statistical analysis, and numerical modeling. It supports various data formats and offers features that enable efficient data integration, manipulation, and simulation processes. ExactData assists organizations and researchers in streamlining workflows related to data-driven experiments, computational modeling, and result interpretation. The software is suited for use in sectors requiring robust data processing and scientific computing, enabling users to address challenges such as managing large-scale datasets, automating analytical tasks, and improving the accuracy of computational results.
GenRocket is a software platform designed for generating synthetic test data for software development and quality assurance processes. The software provides data generation solutions that enable teams to model, generate, and deliver test data on demand, supporting use cases such as functional testing, integration testing, and performance testing. GenRocket assists organizations in replicating real-world scenarios by allowing users to configure data rules and combinations, facilitating the creation of data sets that comply with specific data privacy regulations. The software integrates with various development and testing tools, supports large-scale data generation, and aims to streamline the test automation process by reducing reliance on production data. GenRocket addresses the challenge of obtaining appropriate test data while maintaining data security and compliance.