Best Test Data Management Tools for MongoDB

CloudTDMS, your one stop for Test Data Management. Discover & Profile your Data, Define & Generate Test Data for all your team members : Architects, Developers, Testers, DevOPs, BAs, Data engineers, and more ... Benefit from CloudTDMS No-Code platform to define your data models and generate your synthetic data quickly in order to get faster return on your “Test Data Management” investments. CloudTDMS automates the process of creating test data for non-production purposes such as development, testing, training, upgrading or profiling. While at the same time ensuring compliance to regulatory and organisational policies & standards. CloudTDMS involves manufacturing and provisioning data for multiple testing environments by Synthetic Test Data Generation as well as Data Discovery & Profiling. CloudTDMS is a No-code platform for your Test Data Management, it provides you everything you need to make your data development & testing go super fast! Especially, CloudTDMS solves the following challenges : -Regulatory Compliance -Test Data Readiness -Data profiling -Automation

IRI FieldShield® is a powerful and affordable data discovery and de-identification package for masking PII, PHI, PAN and other sensitive data in structured and semi-structured sources. Front-ended in a free Eclipse-based design environment, FieldShield jobs classify, profile, scan, and de-identify data at rest (static masking). Use the FieldShield SDK or proxy-based application to secure data in motion (dynamic data masking). The usual method for masking RDB and other flat files (CSV, Excel, LDIF, COBOL, etc.) is to classify it centrally, search for it globally, and automatically mask it in a consistent way using encryption, pseudonymization, redaction or other functions to preserve realism and referential integrity in production or test environments. Use FieldShield to make test data, nullify breaches, or comply with GDPR. HIPAA. PCI, PDPA, PCI-DSS and other laws. Audit through machine- and human-readable search reports, job logs and re-ID risks scores. Optionally mask data when you map it; FieldShield functions can also run in IRI Voracity ETL and federation, migration, replication, subsetting, and analytic jobs. To mask DB clones run FieldShield in Windocks, Actifio or Commvault. Call it from CI/CD pipelines and apps.

Data management software is predominantly utilized by enterprise business teams, necessitating a design that prioritizes user-friendliness, automation, and intelligence. Furthermore, it is essential for the software to comply with a variety of industry-specific regulations and data protection mandates. To ensure that business teams can make informed, data-driven strategic decisions, the data must maintain standards of adequacy, accuracy, consistency, high quality, and secure accessibility. The software promotes an integrated methodology for managing data privacy, ensuring data quality, overseeing test data management, facilitating data analytics, and supporting data modeling. Additionally, it effectively manages escalating data volumes through a service engine-based architecture, while also addressing specialized data processing needs beyond standard functionalities via a user-defined function framework and Python adapter. Moreover, it establishes a streamlined governance framework that focuses on data privacy and quality management, enhancing overall data integrity. As a result, organizations can confidently rely on this software to support their evolving data requirements.

Delphix is the industry leader for DataOps. It provides an intelligent data platform that accelerates digital change for leading companies around world. The Delphix DataOps Platform supports many systems, including mainframes, Oracle databases, ERP apps, and Kubernetes container. Delphix supports a wide range of data operations that enable modern CI/CD workflows. It also automates data compliance with privacy regulations such as GDPR, CCPA and the New York Privacy Act. Delphix also helps companies to sync data between private and public clouds, accelerating cloud migrations and customer experience transformations, as well as the adoption of disruptive AI technologies.

Tonic provides an automated solution for generating mock data that retains essential features of sensitive datasets, enabling developers, data scientists, and sales teams to operate efficiently while ensuring confidentiality. By simulating your production data, Tonic produces de-identified, realistic, and secure datasets suitable for testing environments. The data is crafted to reflect your actual production data, allowing you to convey the same narrative in your testing scenarios. With Tonic, you receive safe and practical data designed to emulate your real-world data at scale. This tool generates data that not only resembles your production data but also behaves like it, facilitating safe sharing among teams, organizations, and across borders. It includes features for identifying, obfuscating, and transforming personally identifiable information (PII) and protected health information (PHI). Tonic also ensures the proactive safeguarding of sensitive data through automatic scanning, real-time alerts, de-identification processes, and mathematical assurances of data privacy. Moreover, it offers advanced subsetting capabilities across various database types. In addition to this, Tonic streamlines collaboration, compliance, and data workflows, delivering a fully automated experience to enhance productivity. With such robust features, Tonic stands out as a comprehensive solution for data security and usability, making it indispensable for organizations dealing with sensitive information.

Syntho is generally implemented within our clients' secure environments to ensure that sensitive information remains within a trusted setting. With our ready-to-use connectors, you can establish connections to both source data and target environments effortlessly. We support integration with all major databases and file systems, offering more than 20 database connectors and over 5 file system connectors. You have the ability to specify your preferred method of data synthetization, whether it involves realistic masking or the generation of new values, along with the automated identification of sensitive data types. Once the data is protected, it can be utilized and shared safely, upholding compliance and privacy standards throughout its lifecycle, thus fostering a secure data handling culture.