Fake JSON Server
A .NET-based fake REST API server for prototyping and CRUD backends, with GraphQL support and no database required.
What is Fake JSON Server?
Fake JSON Server is a .NET-based fake REST API server that simulates a backend without requiring a database. It uses a single JSON file for data storage and dynamically generates API endpoints for prototyping, testing, or as a starting point for CRUD backends. It also includes experimental GraphQL support and features like authentication, pagination, and WebSocket notifications.
Developers and teams needing a quick, configurable mock backend for frontend prototyping, API testing, or as a reference implementation for building RESTful services in .NET.
It offers a zero-configuration, dynamic API with comprehensive REST features and GraphQL support, all without a database, making it ideal for rapid development and testing scenarios.
Overview
Fake JSON Server is a Fake REST API that can be used as a Back End for prototyping or as a template for a CRUD Back End.
Use Cases
Best For
- Prototyping frontend applications without a real backend
- Testing API integrations and client-side code
- Creating mock backends for development and staging environments
- Learning REST API best practices with a reference implementation
- Building CRUD backends quickly using the provided template
- Simulating network conditions with configurable delays and errors
Not Ideal For
- Production deployments requiring scalable database persistence and high concurrency
- Applications needing complex server-side business logic or validation beyond basic CRUD operations
- Projects that rely on relational data features like joins, transactions, or advanced querying beyond JSON filtering
- Real-time systems requiring robust WebSocket support beyond simple update notifications
Pros & Cons
Pros
Requires no database installation or route definitions; just start the server with a JSON file, and dynamic API endpoints are generated instantly, as highlighted in the README's 'No setup required' principle.
Supports full CRUD operations with proper HTTP status codes, plus pagination, filtering, sorting, authentication, and content negotiation, following REST best practices compiled from multiple guides.
Runs on Windows, Linux, and macOS via .NET CLI, Docker, or self-contained executables, with no prerequisites, making it accessible for diverse development environments.
Includes configurable request delays and random error injection in appsettings.json, allowing developers to simulate network conditions and test error handling seamlessly.
Cons
Relies on a single JSON file for storage, which can become a bottleneck for large datasets, lacks transaction support, and may struggle with concurrent writes, as admitted in the README's performance notes.
GraphQL implementation is marked as experimental and has limitations, such as not supporting updates to child arrays, making it unreliable for production GraphQL needs.
With eager data reload enabled by default, every request reads from the JSON file, potentially slowing down performance with frequent updates or large files, though this can be disabled at a cost.
Frequently Asked Questions
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