When should you consider it?
Best for teams that need smaller, realistic copies of existing application databases with sensitive fields transformed and relationships preserved.
Editorial fit assessment based on the sources below.What are the limits?
It works from existing source data; use a from-scratch generator when the target schema has no representative source records. Connector support for subsetting varies.
Which capabilities are documented?
Documented means a cited vendor source describes this scoped capability. Not verified means the reviewed evidence cannot establish it. Neither is a hands-on test result.
How is it deployed and licensed?
Current public product pages describe the Structural product but do not establish a single deployment model; confirm hosting options with Tonic.
Current public pricing and licensing terms were not established from the reviewed product documentation; contact Tonic for a quote.
Sources and scope
- Tonic Structural | Test Data Management & Data Masking
Product positioning, masking techniques, and the distinction from from-scratch generation.
Source checked: 2026-10-01 - About subsetting | Tonic Structural documentation
Structural subsetting uses configured filters on target tables to form a related subset.
Source checked: 2026-10-01 - Table filtering for data warehouses and Spark-based data connectors
Some Structural connectors do not support subsetting, so avoid universal connector claims.
Source checked: 2026-10-01
What should you verify in a proof of concept?
- Your database version, schema constraints and target formats.
- The exact product, edition, deployment and license entitlements.
- Your business assertions and the meaning of repeatability for your output.
- A failed run, cleanup and a repeat run on controlled inputs.