Faker.js vs Snowfakery
Faker.js
fakerjs.devSnowfakery
snowfakery.readthedocs.ioSide by side
| Figure | Faker.js | Snowfakery |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Linux | — | Yes |
| API | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · Test Data Generation Tools | 7.5 (#16) | 7.9 (#8) |
| Installation | The guide documents installation through npm, pnpm, yarn, and Deno. | The documentation instructs non-Salesforce users to install Snowfakery with pipx and recommends installing CumulusCI for Salesforce use. |
| Purpose | Faker generates fake but realistic data for testing and development. | Snowfakery generates unique, random fake data with relationships between tables from YAML recipe files. |
Plans
In their own words
Faker.js
Faker.js is a free JavaScript library for generating synthetic data that resembles realistic information during testing and development. Its modules produce person, location, date, finance, commerce, and other data. Documented uses include unit tests, performance tests, demos, and development before a backend is complete. Pre-built instances cover more than 70 locales, and custom locales can be created. The implementation runs in browsers and Node.js; Faker v10 requires Node.js 20 or newer. Installation guidance covers npm, pnpm, yarn, and Deno, with examples for Vitest, Jest, Cypress, and Playwright. A seed can make generated values repeatable, although identical seeds may produce different results between Faker versions. The full package exceeds 5 MiB when minified, and its guide advises against deploying the entire package in a web app. Locale coverage varies, with some combinations using English fallback data or lacking applicable data. Faker is MIT licensed for commercial and non-commercial use and is self-hosted.
Snowfakery
Snowfakery generates synthetic data from YAML recipe files, including records linked across tables. Recipes can create names, addresses, text, URLs, random numbers and other values using Faker-based functions, and specify how many related objects to generate. Output can go to files in JSON, TXT, CSV, SQL, DOT, SVG, SVGZ, JPEG and PostScript formats; some diagram formats require Graphviz. Snowfakery can also write to databases accessible through SQLAlchemy, including SQLite, and generate records in Salesforce when used through CumulusCI. Python applications can embed it with its generate_data function, and Python plugins and providers can extend its functions and Faker capabilities. Strict mode checks a recipe before generation, while validate-only mode checks it without generating data. It is free, open source and self-hosted. The documentation says database output creates new tables, with generated columns as text, and that SQLite is the only database included in its SQL dataset URL test suite. The repository was archived on September 18, 2026, and is read-only.