Faker is a Ruby library that generates fake data such as names, addresses, phone numbers, and more for testing and seeding databases.
Best MOSTLY AI Alternatives ranked by AI · updated Aug 2026
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MOSTLY AI is an enterprise platform for generating synthetic tabular, time-series, and relational data. It targets organizations that need realistic privacy-preserving data for analytics, testing, and machine learning.
Top 6 MOSTLY AI alternatives
Tonic is a comprehensive software solution for data masking and de-identification. It helps businesses protect sensitive data by anonymizing personally identifiable information.
Starting at $500/month
Statice is a privacy-preserving data platform for generating synthetic datasets and enabling controlled data collaboration. It is designed for enterprises handling sensitive...
Pros
- Supports synthetic data generation for sensitive enterprise datasets
- Includes privacy-focused controls for data sharing and collaboration
- More suited to regulated organizations than general-purpose data tools
Cons
- Less accessible to individuals and small teams than open-source alternatives
- Custom enterprise pricing makes costs difficult to compare
- Smaller ecosystem and community than SDV or YData
Custom pricing
Gretel is a synthetic data platform for developers, data scientists, and privacy teams. It generates, transforms, and evaluates synthetic datasets for machine...
Pros
- Supports tabular, text, and time-series synthetic data generation
- Provides privacy and quality evaluation tools alongside generation
- Offers APIs and SDKs suited to automated data pipelines
Cons
- Advanced usage can become expensive compared with self-hosted tools
- Requires synthetic-data expertise to validate utility and privacy claims
- Less focused on visual data preparation than dedicated data-wrangling platforms
Free tier; paid plans with custom pricing
Seedata is a data-generation platform for developers and teams that need realistic synthetic data for testing, development, and analysis. It focuses on...
Pros
- Designed specifically for synthetic test-data workflows
- Can reduce exposure of sensitive production data
- More focused on structured data generation than general-purpose mocking tools
Cons
- Smaller ecosystem than Faker or Mockaroo
- Less established enterprise track record than Tonic or Mostly AI
- Pricing and plan details are not clearly available
6
Gretel
Gretel Labs
Gretel provides APIs and tools for generating synthetic data, transforming sensitive datasets, and evaluating privacy and utility. It is aimed at developers...
Pros
- Developer-friendly APIs and hosted workflows
- Supports more data types than many tabular-only competitors
- Built-in privacy and quality evaluation tools
Cons
- Usage-based costs can be harder to predict at scale
- Advanced governance is more enterprise-oriented than SDV
- May require more platform integration work than an all-in-one suite
Free tier; paid usage and enterprise plans
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