Snaplet Seed vs Tonic.ai
Feature checklists rarely decide anything. What decides it is the pricing metric, who has to write the tests, and which limitation you can live with.
Entry price
Free and open source
Open sourceQuote on request
Quote onlyWhat drives the bill
The metric that actually scales your invoice.
Free and MIT-licensed. Snaplet the company shut down in August 2024 and snaplet.dev no longer resolves; this is a community-held library, not a service.
Enterprise quote-based pricing by data volume and connected databases.
Free tier
Everything, self-hosted
Free trial.
Open source
MIT
Self-hostable
No-code authoring
Languages
Platforms
Fits teams
Adoption
Emerging
Supabase community (formerly Snaplet) · since 2021
Established
Tonic.ai · since 2018
Strengths
- Schema-aware generation means the data actually inserts and the app actually works.
- Deterministic seeds make failing tests reproducible.
- Good TypeScript ergonomics with Prisma and Drizzle.
- 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.
Limitations
- Effectively unmaintained: the last npm release (0.98.0) was July 2024 and the last commit to the default branch was August 2024, though the repo is not archived.
- PostgreSQL-centric.
- TypeScript ecosystem only.
- 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.
Best for
TypeScript teams that want each developer and CI run to start from a clean, coherent database.
Organisations that currently copy production data into staging and know they should stop.
All of these integrate with: PostgreSQL.
Pricing last reviewed August 2026 and is indicative only — confirm on each vendor’s own page.