Test Data Management for Enterprise Apps & Databases

What if your tests adapted automatically?

Connect data source

Create workflow & run job

Set up your test data workflow in minutes—choose the intuitive visual editor for a guided, no-code experience, or use the powerful CLI for full control and automation.

Deploy to test environment

Deploy your prepared test data into any test or pre-production environment. Integrate with your CI/CD pipeline for continuous, automated updates, ensuring your teams always have secure, production-like data for development, QA, and load testing.

What if your tests adapted automatically?

Connect data source

Connect to your data in the way that works best for your workflow: link a database schema, upload a database sample, integrate directly with your application via API, or securely connect to your full production database through an API. Synthesized supports a wide range of databases and input types, making it easy to get started with your real data, wherever it resides.

Create workflow & run job

Set up your test data workflow in minutes—choose the intuitive visual editor for a guided, no-code experience, or use the powerful CLI for full control and automation. Easily configure masking, subsetting, or data generation steps, then run jobs to automatically transform and synthesize high-quality, compliant test data—no manual scripting required.

Deploy to test environment

One platform Supporting Complex Enterprise Database Needs

Remove the data bottleneck in SAP HANA testing

SAP HANA testing is often slowed down by complex, tightly integrated data that’s difficult to validate without impacting business continuity. Synthesized provides SAP-native test data management and automation to deliver reliable, production-scale data across SAP and non-SAP systems.

Deliver production-scale, compliant test data for every testing scenario
Validate end-to-end processes across SAP HANA and connected applications
Reduce risk and accelerate SAP changes with reliable test data

Stream PostgreSQL database preparation for development and testing

Synthesized provides the only AI-driven database masking, subsetting, and generation for PostgreSQL, tailored for application development and testing teams.

Automate the creation of databases that closely mirror production environments.
Enhance security and compliance by intelligently masking sensitive data, ensuring that personally identifiable information is protected.

Automate SQL Server test data provisioning

Synthesized optimizes SQL Server development cycles by efficiently identifying performance bottlenecks and data anomalies, crucial for handling large transaction volumes and complex queries.

Ensure every possible data scenario is covered by your test data.
Identify the "unknown unknowns", to accelerate release cycles and deliver with fewer bugs.

Microsoft SQL Server test data in Synthesized

Automated test data provisioning for Oracle

Synthesized for Oracle databases enhance environments that handle high-volume transactions and complex production pipelines. Minimize downtime and optimize development with the right data, not all the data.

Manage complex Oracle-specific data types and relationships with Synthesized automated data generation
Intelligent masking for PII risk discovery.

Oracle Database test data in Synthesized

Enhance Salesforce development with privacy-preserving snapshots

Synthesized enables rapid, reliable Salesforce application development with privacy-preserving snapshots for QA and development. Quickly identify and resolve issues, minimizing operational disruptions and enhance application robustness before release, not after.

Automated, comprehensive data coverage for any use-case
Protect sensitive customer information with AI-driven data masking techniques, ensuring compliance with codified regulatory rules

Generate

AI-powered test data generation

High quality, production realistic test data generation. Design, generate and provision unlimited test-case specific datasets on-demand - in minutes - enabling continuous testing and AI-driven DevOps acceleration.

Mask

Eliminate data breach risk

Ensure regulatory compliance and reduce risk with AI-first test data automation that identifies, masks and secures sensitive data at scale across environments. Robust annonymization for PII compliance.

Subset

Access the right data, not all the data

Enable secure, role-specific data access with intelligent, automated data subsetting that reduces storage costs and eliminates wait times for new test environments.

MORE THAN JUST FASTER RELEASES

Create data with Synthesized to:

Accelerate cloud and application migration

Overcome fragmented systems with a unified test data platform. Synthesized breaks down data silos, providing seamless integration and a consistent approach to test data management. Flaky tests undermine confidence in automation. Synthesized ensures your test data is stable and reliable, aligning perfectly with your test automation frameworks for consistent results.

Adopt DevOps for your database management

Save over 70% in costs per application dev & test lifecycle. Make your database provisioning cloud-native using Synthesized database generation, masking and subsetting engine that runs in Kubernetes. Seamless integration with testing frameworks enables efficient automation, while continuous learning ensures ongoing improvement, resulting in faster, higher-quality software releases.

Automate test data management with the power of AI

With AI algorithms analyzing requirements and patterns, realistic data is produced, ensuring comprehensive test coverage. Sensitive data is protected through intelligent masking techniques while maintaining data integrity. Test data is dynamically refreshed to reflect changes in the application, and predictive maintenance anticipates future testing needs.

Identify bugs earlier, for faster, more stable releases

Ensure rapid detection, root cause analysis, and resolution of data quality issues, enabling quick mitigation before impacting your operations. Feel confident in your application by finding the root cause before anyone else.

Test data management FAQ

What is test data management (TDM)?

Test data management is how teams create, protect and deliver the data they test against. It covers finding and masking personal data, subsetting large production databases to a useful size, generating synthetic data to fill gaps, and provisioning the result to test environments on demand. Good TDM keeps relationships intact, so tests fail because of defects, not because of broken data.

What is the difference between test data management and data masking?

Data masking is one technique inside test data management. Masking replaces personal and confidential values with realistic substitutes. Test data management covers the whole supply of test data: masking, subsetting, synthetic generation, refreshes, versioning and delivery into environments and pipelines. A team can mask data well and still wait days for each refresh; test data management deals with both problems.

How do you get production-like test data without personal data?

Combine three methods. Mask personal values consistently, so the same customer gets the same replacement in every table and system. Subset production to the business processes you test, keeping linked records complete. Generate synthetic data where no safe real data exists, such as new products or rare edge cases. Apply the same rules to documents and free text, not only to tables.

How does test data management work for SAP?

SAP test data is hard because one business process spans many modules, tables and connected systems. Synthesized masks, right-sizes and generates test data for SAP S/4HANA and ECC without installing anything in SAP. It slices data by business process rather than by date alone, and keeps the same masked customer in SAP and Salesforce, so Order-to-Cash and Procure-to-Pay tests run end to end. See SAP test data.

How does test data management change for AI agents?

Agents act across systems and documents, so masked tables are not enough. They need the same customer consistent across records, emails and PDFs, plus the system state an action depends on, reset for every run. That is the job of a safe-state layer, which Synthesized builds on the same masking, subsetting and generation engine.

What is a safe-state layer? →

How does test data management fit into CI/CD and test automation?

Test data becomes a pipeline step. Masking, subsetting and generation jobs are defined as version-controlled YAML and run from CI/CD tools such as GitHub Actions, GitLab CI, Jenkins or Azure DevOps, for example as a nightly refresh. Test automation tools such as UiPath and Tricentis Tosca get fresh data for each run, so tests do not fail on stale or used-up records.

AI-native test data management for enterprise apps and databases

At the heart of every testing challenge is the quality and accessibility of test data.

What if your tests adapted automatically?

What if your tests adapted automatically?

One platform Supporting Complex Enterprise Database Needs

Remove the data bottleneck in SAP HANA testing

Stream PostgreSQL database preparation for development and testing

Automate SQL Server test data provisioning

Automated test data provisioning for Oracle