zod vs joi vs yup vs superstruct vs io-ts vs arktype vs runtypes
Type Validation Libraries in JavaScript Comparison
1 Year
zodjoiyupsuperstructio-tsarktyperuntypesSimilar Packages:
What's Type Validation Libraries in JavaScript?

Type validation libraries are essential tools in JavaScript development that help ensure data integrity by validating the structure and types of data at runtime. These libraries provide developers with the ability to define schemas for their data, allowing for easier debugging, better error handling, and improved code quality. They are particularly useful in applications where data is received from external sources, such as APIs, and need to be validated before being processed or stored.

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zod31,580,26138,4131.62 MB59619 hours agoMIT
joi12,287,15321,107531 kB190a year agoBSD-3-Clause
yup7,573,75123,394260 kB2466 months agoMIT
superstruct2,770,4767,121182 kB98a year agoMIT
io-ts2,005,7086,779460 kB1646 months agoMIT
arktype278,7336,203327 kB1742 months agoMIT
runtypes190,0962,654312 kB204 months agoMIT
Feature Comparison: zod vs joi vs yup vs superstruct vs io-ts vs arktype vs runtypes

Type Safety

  • zod:

    Zod is designed with TypeScript in mind, offering first-class support for type inference from schemas. This allows for seamless integration of validation logic with TypeScript types, ensuring type safety throughout the application.

  • joi:

    Joi offers a robust validation API but does not provide direct TypeScript type inference. However, it allows for defining schemas that can be used to validate data effectively, though additional TypeScript definitions may be required for full type safety.

  • yup:

    Yup allows for schema definitions that can be used for validation, but it does not provide built-in TypeScript type inference. Developers may need to manually define types or use additional libraries to ensure type safety.

  • superstruct:

    Superstruct provides a flexible way to define data structures and validate them at runtime. It supports TypeScript, allowing for type inference from defined structures, but may require additional setup for complex types.

  • io-ts:

    io-ts leverages TypeScript's type system to provide runtime validation that aligns with compile-time types. Its functional approach allows for composable and reusable validation logic, making it a powerful choice for complex data structures.

  • arktype:

    Arctype provides strong type inference capabilities, allowing developers to define schemas that are directly tied to TypeScript types. This ensures that the validation logic is consistent with the types defined in the code, reducing runtime errors.

  • runtypes:

    Runtypes focuses on providing a straightforward way to validate data types while offering TypeScript support. It allows developers to create type-safe runtime checks that align closely with TypeScript definitions, enhancing type safety.

Ease of Use

  • zod:

    Zod features a straightforward API that is easy to use, especially for TypeScript developers, allowing for quick schema definitions and validations.

  • joi:

    Joi is known for its user-friendly, fluent API that allows developers to chain validation rules easily, making it one of the most approachable libraries for beginners and experienced developers alike.

  • yup:

    Yup has a simple and expressive API that is particularly well-suited for form validation, making it easy to integrate into React applications and other frameworks.

  • superstruct:

    Superstruct provides a clear and concise API that is easy to learn, allowing developers to define structures and validations quickly, making it suitable for rapid development.

  • io-ts:

    io-ts requires a functional programming mindset, which may have a steeper learning curve for some developers. However, once understood, it provides powerful tools for validation and type checking.

  • arktype:

    Arctype has a clean and intuitive API that simplifies the process of defining and validating schemas, making it accessible for developers of all skill levels.

  • runtypes:

    Runtypes offers a simple and straightforward API that is easy to understand and use, making it a good choice for developers who want quick and effective validation without complexity.

Performance

  • zod:

    Zod is built with performance in mind, ensuring that validation checks are fast and efficient, making it a great choice for applications that require quick data validation.

  • joi:

    Joi is generally performant, but complex validation schemas with many nested rules can lead to slower performance. Developers should be mindful of this when designing their validation logic.

  • yup:

    Yup is optimized for performance, especially in form validation scenarios, where it can efficiently handle large amounts of data without significant slowdowns.

  • superstruct:

    Superstruct is designed to be efficient, allowing for quick validation checks while providing flexibility in defining validation logic, making it a good choice for performance-sensitive applications.

  • io-ts:

    io-ts is designed to be efficient, but its functional programming style may introduce some overhead compared to more straightforward libraries. However, it remains performant for most use cases.

  • arktype:

    Arctype is optimized for performance, ensuring that validation checks are efficient and do not introduce significant overhead, making it suitable for high-performance applications.

  • runtypes:

    Runtypes is lightweight and designed for performance, providing fast validation checks without unnecessary overhead, making it suitable for performance-critical applications.

Integration

  • zod:

    Zod is designed for TypeScript-first projects and integrates well with modern frameworks, providing a seamless experience for developers looking to implement validation.

  • joi:

    Joi is widely used in Node.js applications and integrates well with frameworks like Express, making it a popular choice for backend validation.

  • yup:

    Yup is particularly well-suited for React applications, offering strong integration with form libraries like Formik and React Hook Form, making it a popular choice for frontend validation.

  • superstruct:

    Superstruct is designed to be flexible and can be integrated into various projects, including React and Node.js applications, providing a straightforward way to validate data.

  • io-ts:

    io-ts can be integrated into various frameworks, but its functional programming style may require additional effort to adapt to certain environments. It works well with TypeScript and functional programming paradigms.

  • arktype:

    Arctype integrates seamlessly with TypeScript, making it an excellent choice for TypeScript-heavy projects, and can be easily used with various frameworks and libraries.

  • runtypes:

    Runtypes can be easily integrated into any JavaScript or TypeScript project, providing a simple way to validate data structures without significant overhead.

How to Choose: zod vs joi vs yup vs superstruct vs io-ts vs arktype vs runtypes
  • zod:

    Opt for Zod if you want a TypeScript-first schema declaration and validation library that emphasizes simplicity and type inference, making it an excellent choice for TypeScript-heavy projects.

  • joi:

    Opt for Joi if you are looking for a mature, feature-rich validation library with a fluent API that is easy to use and integrates well with various frameworks, making it suitable for both backend and frontend validation.

  • yup:

    Select Yup if you prefer a schema builder for value parsing and validation that is particularly well-suited for form validation in React applications, offering a simple API and strong integration with form libraries.

  • superstruct:

    Choose Superstruct if you need a flexible and powerful validation library that allows for custom validation logic and is designed to work well with both TypeScript and JavaScript, making it suitable for a wide range of applications.

  • io-ts:

    Select io-ts if you prefer a functional programming approach to validation and want to leverage TypeScript's type system for runtime type checking, especially if you're working with complex nested structures.

  • arktype:

    Choose Arktype if you need a library that focuses on type-safe runtime validation with a strong emphasis on TypeScript integration, allowing for seamless type inference and a more robust development experience.

  • runtypes:

    Consider Runtypes if you want a lightweight library that provides a simple and straightforward way to validate data types with TypeScript support, focusing on ease of use and minimal overhead.

README for zod

Zod logo

Zod

TypeScript-first schema validation with static type inference
by @colinhacks


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Read the docs →



What is Zod?

Zod is a TypeScript-first validation library. Define a schema and parse some data with it. You'll get back a strongly typed, validated result.

import { z } from "zod/v4";

const User = z.object({
  name: z.string(),
});

// some untrusted data...
const input = {
  /* stuff */
};

// the parsed result is validated and type safe!
const data = User.parse(input);

// so you can use it with confidence :)
console.log(data.name);

Features

  • Zero external dependencies
  • Works in Node.js and all modern browsers
  • Tiny: 2kb core bundle (gzipped)
  • Immutable API: methods return a new instance
  • Concise interface
  • Works with TypeScript and plain JS
  • Built-in JSON Schema conversion
  • Extensive ecosystem

Installation

npm install zod

Basic usage

Before you can do anything else, you need to define a schema. For the purposes of this guide, we'll use a simple object schema.

import { z } from "zod/v4";

const Player = z.object({
  username: z.string(),
  xp: z.number(),
});

Parsing data

Given any Zod schema, use .parse to validate an input. If it's valid, Zod returns a strongly-typed deep clone of the input.

Player.parse({ username: "billie", xp: 100 });
// => returns { username: "billie", xp: 100 }

Note — If your schema uses certain asynchronous APIs like async refinements or transforms, you'll need to use the .parseAsync() method instead.

const schema = z.string().refine(async (val) => val.length <= 8);

await schema.parseAsync("hello");
// => "hello"

Handling errors

When validation fails, the .parse() method will throw a ZodError instance with granular information about the validation issues.

try {
  Player.parse({ username: 42, xp: "100" });
} catch (err) {
  if (error instanceof z.ZodError) {
    err.issues;
    /* [
      {
        expected: 'string',
        code: 'invalid_type',
        path: [ 'username' ],
        message: 'Invalid input: expected string'
      },
      {
        expected: 'number',
        code: 'invalid_type',
        path: [ 'xp' ],
        message: 'Invalid input: expected number'
      }
    ] */
  }
}

To avoid a try/catch block, you can use the .safeParse() method to get back a plain result object containing either the successfully parsed data or a ZodError. The result type is a discriminated union, so you can handle both cases conveniently.

const result = Player.safeParse({ username: 42, xp: "100" });
if (!result.success) {
  result.error; // ZodError instance
} else {
  result.data; // { username: string; xp: number }
}

Note — If your schema uses certain asynchronous APIs like async refinements or transforms, you'll need to use the .safeParseAsync() method instead.

const schema = z.string().refine(async (val) => val.length <= 8);

await schema.safeParseAsync("hello");
// => { success: true; data: "hello" }

Inferring types

Zod infers a static type from your schema definitions. You can extract this type with the z.infer<> utility and use it however you like.

const Player = z.object({
  username: z.string(),
  xp: z.number(),
});

// extract the inferred type
type Player = z.infer<typeof Player>;

// use it in your code
const player: Player = { username: "billie", xp: 100 };

In some cases, the input & output types of a schema can diverge. For instance, the .transform() API can convert the input from one type to another. In these cases, you can extract the input and output types independently:

const mySchema = z.string().transform((val) => val.length);

type MySchemaIn = z.input<typeof mySchema>;
// => string

type MySchemaOut = z.output<typeof mySchema>; // equivalent to z.infer<typeof mySchema>
// number