Pros of Yup

• More mature and established library with a longer history
• Extensive documentation and community support
• Supports asynchronous validation out of the box

Cons of Yup

• Larger bundle size compared to Zod
• Less TypeScript-friendly, with some type inference limitations
• Slower performance in certain scenarios

Code Comparison

Yup:

import * as Yup from 'yup';

const schema = Yup.object().shape({
  name: Yup.string().required(),
  age: Yup.number().positive().integer().required(),
});

Zod:

import { z } from 'zod';

const schema = z.object({
  name: z.string(),
  age: z.number().positive().int(),
});

Both libraries offer similar functionality for defining and validating schemas. Yup uses a chaining API, while Zod leverages TypeScript's type inference for a more concise syntax. Zod's approach results in better type safety and autocompletion in TypeScript environments.

Yup has been around longer and has more extensive documentation, making it easier for beginners to get started. However, Zod's TypeScript-first approach and smaller bundle size make it an attractive option for modern TypeScript projects, especially those prioritizing performance and type safety.

Pros of Superstruct

• Simpler API with fewer concepts to learn
• More flexible with custom types and validators
• Smaller bundle size, which can be beneficial for frontend applications

Cons of Superstruct

• Less comprehensive type inference compared to Zod
• Fewer built-in validators and data transformation features
• Not as actively maintained as Zod (fewer recent updates)

Code Comparison

Zod:

const UserSchema = z.object({
  name: z.string(),
  age: z.number().min(18),
  email: z.string().email()
});

Superstruct:

const UserSchema = object({
  name: string(),
  age: number().min(18),
  email: string().pattern(/^[^@]+@[^@]+\.[^@]+$/)
});

Both libraries offer similar functionality for defining schemas and validating data. Zod provides more built-in validators (like .email()), while Superstruct requires custom patterns for complex validations. Zod's syntax is slightly more concise, but Superstruct's approach may be more intuitive for some developers.

Pros of io-ts

• More established project with a longer history and larger community
• Offers advanced features like branded types and refinements
• Integrates well with functional programming paradigms

Cons of io-ts

• Steeper learning curve, especially for developers new to functional programming
• Less intuitive syntax compared to Zod
• Slower runtime performance in some scenarios

Code Comparison

io-ts:

import * as t from 'io-ts'

const User = t.type({
  name: t.string,
  age: t.number
})

type User = t.TypeOf<typeof User>

Zod:

import { z } from 'zod'

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

type User = z.infer<typeof User>

Both libraries provide runtime type checking and static type inference. io-ts uses a more functional approach with its t.type and t.TypeOf constructs, while Zod offers a more straightforward, object-oriented syntax. Zod's API is generally considered more intuitive for developers familiar with TypeScript's built-in type system.

While io-ts excels in advanced type manipulation and functional programming patterns, Zod has gained popularity due to its ease of use and performance. The choice between the two often depends on the project's requirements and the team's familiarity with functional programming concepts.

Pros of Runtypes

• Simpler API with fewer methods, making it easier to learn and use
• Supports recursive types out of the box
• Smaller bundle size, which can be beneficial for frontend applications

Cons of Runtypes

• Less active development and community support compared to Zod
• Fewer built-in validations and transformation options
• Limited documentation and examples available

Code Comparison

Zod:

const UserSchema = z.object({
  name: z.string(),
  age: z.number().min(18),
  email: z.string().email()
});

Runtypes:

const User = Record({
  name: String,
  age: Number.withConstraint(n => n >= 18),
  email: String.withConstraint(s => /@/.test(s))
});

Both libraries provide runtime type checking and validation, but Zod offers more built-in validators (like .email()), while Runtypes requires custom constraints for complex validations. Zod's API is more extensive, offering additional features like transformations and error customization, whereas Runtypes focuses on a simpler, more straightforward approach to runtime type checking.

Pros of Ajv

• Higher performance and faster validation, especially for large datasets
• Supports JSON Schema standard, making it more versatile for existing schemas
• More mature project with a larger ecosystem and wider adoption

Cons of Ajv

• More complex API and steeper learning curve
• Less TypeScript-friendly, requiring additional type annotations
• Larger bundle size, which may impact client-side applications

Code Comparison

Ajv:

const Ajv = require("ajv")
const ajv = new Ajv()

const schema = {
  type: "object",
  properties: {
    foo: { type: "integer" },
    bar: { type: "string" }
  },
  required: ["foo"],
  additionalProperties: false
}

const validate = ajv.compile(schema)

Zod:

import { z } from "zod"

const schema = z.object({
  foo: z.number().int(),
  bar: z.string().optional()
})

const result = schema.safeParse(data)

Ajv uses JSON Schema syntax and requires compilation, while Zod offers a more concise and TypeScript-native approach. Zod's API is generally easier to understand and use, especially for TypeScript developers. However, Ajv's performance advantages and JSON Schema compatibility make it a strong choice for certain use cases, particularly when dealing with large datasets or existing JSON Schema definitions.