What is CTGAN?
An open-source synthetic data generator that uses Conditional GANs to learn patterns from real tabular data and produce high-fidelity synthetic versions for analysis and testing.
CTGAN pricing
We don't have CTGAN's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
What CTGAN does
The capabilities that matter for synthetic data, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Generation method
- GAN
- Relational integrity
- -
- Differential privacy
- -
- Privacy risk scoring
- -
- Fidelity utility reporting
- ✓
- Masking included
- -
- Deployment
- Self host
- Open source
- ✓
- Ci cd integration
- -
- Industry focus
- Horizontal
- SOC2
- -
- HIPAA available
- -
- Pricing model
- Open source
Platform & deployment
Independently observed- CLI
- Web
- Self-hosted
Integrations (2)
Independently observed- SDV ecosystem
- Python packages
Security & compliance
Known vulnerabilities: 0 (0 in the last 12 months) sourcea count reflects scale & disclosure, not quality
CTGAN FAQ
Common questions about CTGAN, answered from independent, dated evidence.
What is CTGAN?
An open-source tool that learns patterns from real single-table datasets and generates high-quality synthetic data with preserved statistical properties, built on generative adversarial network architecture. It is indexed under Synthetic Data.
Source: https://github.com/pricing
Is CTGAN free to use?
CTGAN is open source, so it can be self-hosted and used at no licence cost. Pricing changes often, so verify at source before relying on it.
Source: https://github.com/pricing
What platforms does CTGAN support?
CTGAN supports a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.
Source: https://github.com/pricing
Can CTGAN be self-hosted?
Yes. CTGAN can be deployed self-hosted, so it does not have to run on the vendor's infrastructure.
Source: https://github.com/pricing
CTGAN alternatives
Other synthetic data we track, ranked by the same independent score.
- Tonic.aiSynthetic data generation platform for accelerating development and testing without exposing sensitive production datahigh · 75%
- YData SyntheticA data platform for creating privacy-compliant synthetic data to improve machine learning model qualitylow · 35%
- K2viewData integration platform that applies privacy controls and governance to enterprise informationlow · 35%
- SarusRepository of classical machine learning models built with TensorFlow and Keraslow · 12%
- SynthoPlatform for generating realistic synthetic test data while preserving data privacy using masking, rule-based, and AI-generated methodslow · 29%
- MOSTLY AISecure access to production data with privacy-protected synthetic data generation for teamslow · 5%
Compare CTGAN
Side by side against other synthetic data, attribute by attribute, with a source on every value.
The vioscaleAI score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for CTGAN, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Release cadence | 61 | 0.08 | 5.0 | ✓ |
| Capabilities | 46 | 0.08 | 3.7 | ✓ |
| Stars | 60 | 0.05 | 2.8 | ✓ |
| Security score | 44 | 0.05 | 2.4 | ✓ |
| Development activity | 15 | 0.14 | 2.0 | ✓ |
| Dependent projects | 25 | 0.05 | 1.3 | ✓ |
| Integrations | 14 | 0.05 | 0.7 | ✓ |
| Security posture | 0 | 0.12 | 0.0 | - |
| Package downloads | 0 | 0.04 | 0.0 | - |
| Developer Q&A activity | 0 | 0.14 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Activity
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 2 | mediumsource · 2026-10-15 · 65% |
Adoption
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 4 items | mediumsource · 2026-09-10 · 60% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Deployment: self_host · Open source: Yes · Pricing model: open_source · Industry focus: horizontal · Generation method: GAN · Fidelity utility reporting: Yes | mediumsource · 2026-10-15 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 2 | mediumsource · 2026-08-21 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | Python | highsource · 2026-10-15 · 90% |
Pricing
Release
Security
| Attribute | Value | Evidence |
|---|---|---|
| Scorecard | 4.4 | highsource · 2026-10-15 · 90% |
| Vulnerabilities | Count: 0 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=ctgan&per_page=100 · Last 12m: 0 | highsource · 2026-10-15 · 90% |
| Trust center | https://github.com/security | mediumsource · 2026-10-15 · 60% |
Is CTGAN the right choice for you?
Tell us the job, the constraints and what you weigh most, and we will rank CTGAN against the rest of the synthetic data we index, using the same dated evidence weighted your way.
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