Gretel.ai vs Snaplet Seed

Quote on request

Free and open source

The old credit-based self-serve tier is gone. The successor microservices are licensed through NVIDIA AI Enterprise; NeMo Data Designer can be tried on build.nvidia.com.

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.

Everything, self-hosted

Emerging

NVIDIA (formerly Gretel) · since 2019

Emerging

Supabase community (formerly Snaplet) · since 2021

• Formal differential-privacy guarantees rather than best-effort masking, now via DP-SGD in NeMo Safe Synthesizer.
• Synthetic data preserves statistical relationships useful for analytics and model training.
• Backed by NVIDIA's platform investment rather than a single startup's runway.

• 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.

• No longer buyable as Gretel — you are procuring NVIDIA AI Enterprise, which is far heavier than the old self-serve signup.
• Model training adds time and cost compared to rule-based masking.
• Safe Synthesizer trains on a real dataset, so it does not help with greenfield data that does not exist yet.

• 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.

Regulated enterprises already standardising on NVIDIA AI Enterprise. Teams that wanted Gretel's self-serve tier should look at Tonic or Neosync instead.

TypeScript teams that want each developer and CI run to start from a clean, coherent database.