Faker vs Tonic.ai

Free and open source

Quote on request

Free and open source. You pay in engineering time and CI minutes.

Enterprise quote-based pricing by data volume and connected databases.

Everything, self-hosted

Free trial.

Category standard

OSS community · since 2010

Established

Tonic.ai · since 2018

• Realistic, locale-aware data catches layout bugs that 'test test test' never will.
• Seedable, so generated data is reproducible when a test fails.
• Available in every major language with a similar API.

• Preserves referential integrity and statistical distribution, so applications behave as they do in production.
• Directly addresses the GDPR and HIPAA exposure created by production data in lower environments.
• Subsetting produces a small but coherent slice rather than a full copy.

• Generated data has no referential integrity or business rules — that is your job.
• Random data makes failures harder to reproduce unless you seed deliberately.
• Not a substitute for production-shaped data at realistic volume.

• Expensive, with enterprise-only pricing.
• Initial configuration of sensitive-field classification takes real effort.
• Adds a pipeline stage that must be maintained as the schema evolves.

Every project that needs fixtures more realistic than placeholder strings.

Organisations that currently copy production data into staging and know they should stop.