Comparison
NexusMock vs Gretel.
Finished CSVs vs the SDK you have to learn first.
Gretel is the developer-first take on synthetic data. You install their SDK, you write a few lines of Python, you train models on your own data or use their pre-trained generators. It is well documented, has a free tier, and is a credible product. It is also the wrong tool when what you actually need is a labelled CSV on disk in the next 60 seconds.
TL;DR
Gretel is a generator framework with a developer-friendly API. NexusMock is the output. If you want to learn synthetic data engineering and integrate generation into your pipeline, Gretel is excellent. If you want a labelled dataset to train a model this afternoon, NexusMock is faster and cheaper at the entry point.
Feature-by-feature
What you actually get.
What you buy
- NexusMock
- A finished CSV with labels
- Gretel
- API access and an SDK to generate your own
Free tier
- NexusMock
- 100-row sample per vertical
- Gretel✓
- 100k rows/month on shared model
Time to first labelled CSV
- NexusMock✓
- 30 seconds (download)
- Gretel
- 30 minutes — install SDK, learn API, generate, save
Labelled fraud typologies
- NexusMock✓
- 5 typologies pre-labelled with documented signatures
- Gretel
- You define and label them yourself
Integration with your pipeline
- NexusMock
- It is a CSV — you `pd.read_csv()` it
- Gretel✓
- First-class — Python SDK, REST API, CLI
Customisation depth
- NexusMock
- Custom variant in 5–10 business days (Enterprise)
- Gretel✓
- Fully programmable — define any schema
Documentation depth (for the data)
- NexusMock✓
- Per-release README, AUC, integrity, Benford
- Gretel
- Per-platform docs; data quality is your job
Price for 100k labelled fraud rows
- NexusMock
- 79 € one-time
- Gretel
- Pay-per-generation credits — depends on model and config
Used by
- NexusMock
- ML engineers bootstrapping a model now
- Gretel
- Data engineers building synthetic generation pipelines
When each one is right
Pick the one that matches your situation.
Pick NexusMock when…
- You want a labelled CSV right now without writing code.
- Your vertical is one of the 5 we already ship.
- You want a one-off purchase, not metered credits.
- Documented quality (AUC, integrity, Benford) matters for your audit trail.
Pick Gretel when…
- You need synthetic data generated programmatically inside your pipeline.
- You want to define a schema we don't ship yet.
- You are building a product that incorporates synthetic generation as a feature.
- You want fine-grained control over the generator's privacy parameters.
Bottom line
The honest verdict.
Gretel is the right tool when synthetic data generation is part of your product. NexusMock is the right tool when synthetic data is one of your inputs and you want it in 30 seconds instead of 30 minutes. Many teams use both — Gretel for the custom verticals they need long-term, NexusMock to unblock the sprint that ships next week.
Frequent objections
What buyers ask before deciding.
Why not just use Gretel's free tier and skip NexusMock?+
If your team has the Python time to use the SDK, knows synthetic data quality methodology, and your vertical fits Gretel's pre-trained models, you may not need NexusMock. We ship to teams who want the output without the integration.
Could NexusMock be built on top of Gretel?+
No — our generators are custom Python with domain-specific typology injection, deterministic seeds, and documented noise. Gretel's generators are a different architecture. The two pipelines coexist; they don't depend on each other.
Quality comparison?+
Apples and oranges. Gretel's quality is whatever you configure. NexusMock's quality is what we ship in our QUALITY_REPORT for that release. Both can be excellent. Both can underperform. Trust the methodology, not the brand.
Want to test NexusMock before buying?
Download a 100-row sample of any vertical, free, no email required.
Browse the catalog →