Masking, subsetting, and synthesis for NoSQL databases
Yes, a quality test data platform for semi-structured data does exist
Features
All the capabilities you need to generate realistic NoSQL data from real data for streamlined development and testing.
Artificial structure
Automatically handle various data types within the same field across documents via an artificial hybrid document.
Masking
Mask different data types using different rules, even within the same field.
Subsetting
Generate referentially intact subsets of your document-based data sized to your developers’ needs.
The value of synthetic NoSQL data
Developer productivity: Equip development, testing, and QA with quality NoSQL data to speed up your release cycles and get your products to market faster.
Faster time-to-market: Enable shift-left testing and development with realistic NoSQL data for earlier bug detection and product optimization.
Cost savings: Reduce infrastructure costs and eliminate resource-heavy workarounds by streamlining NoSQL test data management.
Compliance: Reduce risk in your engineering org and ensure regulatory compliance by enforcing security policies within fake data generation.
Global enablement: Unblock your off-shore resources by equipping them with synthetic test data that is safe, useful, and accessible across borders.
Essential NoSQL test data applications
- For testing and QA: Generate synthetic NoSQL data that mirrors production to fix your staging environments, catch more bugs, and shorten release cycles.
- For local development: Get smaller, targeted document-based datasets, de-identified on demand, to maximize efficiency and minimize risk.
Tonic integrates with every leading database
Tonic Structural supports leading databases, like MySQL, PostgreSQL, SQL Server, and Oracle, offering seamless synthetic data generation and management for all your development and testing needs.
“Tonic has an intuitive, powerful platform for generating realistic, safe data for development and testing.”
Senthil Padmanabhan
Technical Fellow, VP of Engineering
Resources
Explore our guides on all things synthetic test data, from the various approaches of data masking to how to apply test data best practices in implementing test data management software.
Clinical data extraction: how to unlock critical health information
Managing test data from multiple sources without losing consistency
Test data subsetting strategies for targeted software testing
Creating unstructured files from Fabricate Data Agent generated data
Using real-world data for synthetic data generation with the Fabricate Data Agent
Build better and faster with quality test data today.
Unblock data access, turbocharge development, and respect data privacy as a human right.