JSON Validation

Validating JSON data, is a ubiquitous requirement when building TypeScript/Node applications. The definitive standard for describing the structure and constraints of is JSON Schema (https://json-schema.org/). It is critical to note that JSON Schema is a specification, not a library. Libraries like Ajv and TypeBox are implementations that use this specification for high-speed validation.

Many validation libraries exist (some of which are not fully compliant with the specification). The most common choice in the modern TypeScript ecosystem as of 2025 seems to be Zod.

The libraries listed below represent options for validating JSON data.

Zod

  • Documentation: https://zod.dev/
  • Article: https://betterstack.com/community/guides/scaling-nodejs/zod-explained/
  • Primary Focus: TypeScript-First schema declaration and validation.
  • Pros:
    • Excellent Developer Experience (DX): Simple, intuitive, and designed to work with TypeScript's type system automatically.
    • Automatic Type Inference: Eliminates the need to write types separately, ensuring schema and types are always synchronized.
    • Zero dependencies and a simple "parse or throw" API.
  • Cons:
    • Not natively based on the JSON Schema specification.
    • Slightly slower than hyper-optimized JSON Schema validators (like Ajv) for high-performance needs.
  • Currently the most popular and rapidly growing choice for modern, full-stack TypeScript projects (especially with Next.js).

Joi

  • Documentation: https://joi.dev/
  • Article: https://betterstack.com/community/guides/scaling-nodejs/joi-explained/
  • Primary Focus: JavaScript-First schema description and data validation, primarily used for Node.js backends.
  • Pros:
    • Battle-Tested and Mature: The library has been around the longest and has a vast community and feature set.
    • Extremely rich and comprehensive validation API.
    • Robust documentation and strong adoption in existing Node.js applications (often with Express/Hapi).
  • Cons:
    • Requires extra effort and/or third-party tools (like joi-to-typescript) to achieve full TypeScript type safety.
    • Can be verbose for schema definition.

Yup

  • Documentation: https://github.com/jquense/yup
  • Article: https://betterstack.com/community/guides/scaling-nodejs/yup-validation/
  • Inspired by Joi, but Yup is optimized for client-side use.
  • Pros:
    • Lightweight and fast for small-to-medium datasets.
    • Seamless integration with form libraries like Formik and React Hook Form.
  • Cons:
    • Generally the slowest of the major libraries in large-scale performance benchmarks.
    • Less feature-rich than Joi or Zod for complex backend logic.
  • A very popular and reliable choice for client-side forms and UI validation.

Ajv (Another JSON Schema Validator)

  • Documentation: https://ajv.js.org/guide/why-ajv.html
  • JSON Schema Standard compliance and high-performance validation.
  • Pros:
    • Widely considered the fastest JSON Schema validator in the JavaScript ecosystem.
  • Cons:
    • Writing plain JSON Schema is verbose and less developer-friendly than builder-style APIs.
    • Does not natively infer TypeScript types (requires separate tools).
  • Essential for high-performance APIs, microservice architectures, and systems where schema consistency across multiple languages is required.

TypeBox

  • Documentation: https://github.com/sinclairzx81/typebox
  • Article: https://betterstack.com/community/guides/scaling-nodejs/typebox-explained/
  • Built on top of Ajv.
  • Pros:
    • Allows you to define schemas using a builder pattern (Type.String()) that is fully compliant with the JSON Schema specification.
    • Excellent TypeScript Type Inference derived directly from the JSON Schema.
    • Extremely fast when used with its core JSON Schema validation engine (Ajv).
  • Cons:
    • Validation requires linking to an external validator (like Ajv).
    • The API requires a fundamental understanding of JSON Schema concepts.
  • Perhaps the best choice for developers who require both the standardization of JSON Schema and the type safety of TypeScript.

io-ts

  • Documentation: https://gcanti.github.io/io-ts/
  • Pros:
    • Provides the deepest level of type safety by defining runtime codecs that encode and decode data.
    • Works extremely well with functional programming libraries like fp-ts.
  • Cons:
    • Probably the steepest learning curve among this list, requiring familiarity with functional programming concepts.

Superstruct

Comparison

I couldn't find any article that compares all of these in one article but there are many articles comparing different options. Here is a list I compiled below.