Bogus vs Snowfakery

Bogus is a fake data generator for C#, F#, and VB.NET, adapted from faker.js. It creates synthetic data for loading databases, user interfaces, and applications during testing. Its documented data generators cover addresses, commerce, companies, databases, dates, finance, names, and internet data; JSON is listed as a supported format. Multiple locales are available, with English used when a locale-specific data set is missing. Developers can seed the randomizer for repeatable output and define object-generation rules with `Faker`, including strict mode, custom instantiation, and completion callbacks. The project also documents a Faker facade and direct use of DataSets. Bogus is distributed as a NuGet package, installed with `Install-Package Bogus`. Minimum requirements are .NET Standard 1.3, .NET Standard 2.0, or .NET Framework 4.0. The package is free, and deployment is self-hosted. Its page offers a Premium license as a way to support the project but gives no price for it.

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.