testdatatools
AI & ML datasets · Enterprise TDM

Syntho

Syntho prepares database test data using learned generation, mock values and masking. Teams configure column settings in a workspace and write results to a destination database. This profile covers the Syntho platform separately from the MOSTLY AI SDK. 1 · 2 · 3

Sources reviewed

Manufacturer / project: Syntho

When does it fit?

Consider it when you need database-derived datasets with different treatments per column. Use representative input for learned patterns and explicit checks for required business cases. 1 · 2 · 3

Fit still depends on your mandatory requirements.

What should you check before choosing?

AI synthesis does not guarantee rare cases or hard business rules. Its documentation expects entity tables with independent rows. Subsetting documentation says Coming Soon; confirm availability in the offered release. Consistent replacements do not prove identical learned datasets. 1 · 2 · 3

What must your PoC prove?

Use a controlled input and a held-out evaluation set. Check rare payment cases, related rows, sensitive values and repeatable replacements separately. Ask for a release-specific subsetting demonstration. No Syntho execution is claimed here.

Acceptance plan, not a product test result. Execution scope and limits.

Deployment and license

Docker Compose self-hosting is documented, with vendor container images and supporting services. Confirm the exact release, resource sizing and source/destination access before installation. 1 · 2

Deployment requires a vendor license key and registry access. Public list prices were not established here; confirm modules, support and renewal terms with Syntho. 1

Confirm the entitled version and operating requirements.

How you work with it

Connect source and destination schemas, then choose learned generation, mocks or masks per column. Inspect outputs and consistency settings. Data export alone does not establish that workspace rules or trained models run elsewhere. 1 · 2 · 3 · 4

Export does not establish compatibility with another runtime.

Documented capabilities

Subsetting / subset planningUnclear
Data virtualizationUnclear

Documentation is not a measured benchmark. Unclear is missing evidence; the comparison matrix explains the gap.

Sources and scope

Sources can cover different releases; they do not establish measured performance.

Open the cited sources (6)
  1. Syntho FAQ: source/destination databases, mocks and constraints

    Source/destination database requirements, mock generation, masking, metadata relationships; not a universal constraints guarantee.

    Source checked: 2026-10-11
  2. Syntho AI synthesize: preparation and limitations

    Learns dominant patterns from entity tables with independent rows; no guarantee for rare cases, hard business rules or full relational logic.

    Source checked: 2026-10-11
  3. Syntho Mask: column-level replacement settings

    Configured masking functions for sensitive columns; not a privacy or anonymization certification.

    Source checked: 2026-10-11
  4. Syntho consistent mapping and its limits

    Consistent replacements for supported mock/mask/hash generators, workspace seed and no guarantee across platform versions, OS or CPU architecture; not learned-dataset byte replay.

    Source checked: 2026-10-11
  5. Syntho Docker Compose deployment

    Self-hosted stack, container-registry access, vendor license key and infrastructure; no list price established.

    Source checked: 2026-10-11
  6. Syntho subsetting: Coming Soon notice

    Public documentation announces reintroduction, so current release availability remains unverified despite described workflow.

    Source checked: 2026-10-11

Use the same acceptance checks for your shortlist