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Benchmark of Node.js validators

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Benchmark of Node.js validators

It is crucial to verify that the user's input matches the business requirements. Validating input data is one of the most common tasks that all systems perform behind the scenes. In the Node.js ecosystem there are multiple options available in the form of NPM packages. Choosing the right package might not be as trivial as it seems. Recently, I've participated in a project that was utilizing a library called myzod. That choice was quite surprising to me, as I already knew about zod, but I had never heard of myzod. I looked it up on the internet. It was a small library, with only one person maintaining it. It had about a hundred stars on Github and a couple of thousands of downloads every month on NPM. The choice was more surprising as there are many more popular libraries with larger community base and more functionalities. I've asked the team members what was the main reason they decided to pick myzod — it's for performance, they said. Author of myzod states that their solution is about 25 times faster than zod and 6 times faster than Joi. Those benchmarks were performed on Node 13. As of today (December 2023), Node 20 is the latest LTS version of Node.js. Zod and Joi are being actively developed, while myzod seems to be less maintained. I've decided to verify if myzod is still holding up to the author's performance claim.

Tested libraries

Benchmark implementation

Two variants were checked:

  1. Validating only the object structure without verifying the actual content (similar to the benchmarks implemented by the myzod team).
  2. All actual content is checked against the provided criteria in a more realistic example.

All the benchmarks were done on a 2023 MacBook Pro with the Apple M3 Chip using Node 20.10.0 and a tool made by Paolo Insogna, Cronometro. The implementation can be found in the GitHub repository.

Tested object

export const user = {
  name: {
    first: 'John',
    last: 'Doe'
  },
  login: {
    email: 'john.doe@example.com',
    password: 'dcJERRB28hApdfX3puKHkNaEp2KxMa'
  },
  organization_id: 'e923adb7-67e4-428e-98b5-0799c6e93c6f',
  requested_at: '2023-11-18T19:05:46.760Z'
}

In a types only scenario, only the object structure is checked and all the end fields need to be of type string. In comprehensive validation scenario, it is additionally checked if:

  • first name length is between 1 and 999 characters,
  • last name length is between 1 and 999 characters,
  • email contains valid email address,
  • password length is between 12 and 50 characters,
  • organization_id includes valid UUID,
  • requested_at contains date time string satisfying ISO 8601 norm.

Notes on some of the tested libraries

  • myzod does not have refined string validation built-in: "Myzod is not interested in reimplementing all possible string validations, i.e. isUUID, isEmail, isAlphaNumeric, etc. The myzod string validation can be easily extended via the withPredicate API". Implemented benchmarks use validator library because it is used in myzod examples.
  • yup was unable to correctly validate value of requested_at field out of the box . When using yup.date method, yup tries to perform the validation by passing the input into the Date constructor. It results in a faulty validation. For example, string of value: "1" is transformed to Date object 2000-12-31T23:00:00.000Z. Trying to resolve this behavior by enabling strict validation (which disables the casting) results in failed validation in case of string fulfilling the requirements of ISO 8601 norm. To properly validate content of requested_at I decided to combine yup.string with isISO8601 from validator library.

Results

Cronometro outputs summarized test results in a table. More details can be obtained from the results object using the API. Benchmark included 10 000 000 samples and the results were stable.

Types only validation

LibraryResultToleranceDifference with slowest
yup291 522 op/sec± 0.02 %
joi735 207 op/sec± 0.04 %+ 152.20 %
zod1 278 456 op/sec± 0.04 %+ 338.54 %
myzod4 556 899 op/sec± 0.01 %+ 1463.14 %
ajv23 900 990 op/sec± 0.15 %+ 8098.68 %
Types only validation

Comprehensive validation

LibraryResultToleranceDifference with slowest
joi164 668 op/sec± 0.01 %
yup224 323 op/sec± 0.02 %+ 36.23 %
myzod547 872 op/sec± 0.02 %+ 232.71 %
zod928 734 op/sec± 0.03 %+ 464.00 %
ajv2 213 050 op/sec± 0.04 %+ 1243.95 %
Comprehensive validation

In case of only validating the object structure, myzod is about 6 times faster than Joi and almost 3.5 times faster than zod. However, in case of comprehensive validation, myzod is 4 times faster than Joi and almost 2 times slower than zod. I understand that the performance of the validator library greatly influenced the results of this test, but as I mentioned earlier, myzod does not include sophisticated validation methods out of the box. Ajv turned to be the fastest to validate object structure, it's 5 times faster than myzod, and 18 times faster than zod. In the case of comprehensive content validation, Ajv is over 2 times faster than zod.

Additional round of benchmarking

After performing those benchmarks, I've decided to perform an additional test, in which instead of performing 10 000 000 validation rounds on the same object, I've performed 10 000 iterations on 1 000 objects. Objects were generated using the faker library, they had the same structure as the original object.

const users = []

for (let i = 0; i < 1000; i++) {
  users.push({
    name: {
      first: faker.person.firstName(),
      last: faker.person.lastName()
    },
    login: {
      email: faker.internet.email(),
      password: faker.internet.password({ length: getRandomInt(12, 50) })
    },
    organization_id: faker.string.uuid(),
    requested_at: faker.date.anytime().toISOString()
  })
}

Results

The results seem to correspond to the previous test - except Ajv. In case of validating only the object structure (without the actual content) it performed better. In the first benchmark, it took Ajv on average 42 ns to validate an object. In this scenario, Ajv needed, 14175 ns to validate 1 000 objects. It's 14 ns per object, about 4 times faster than in the previous case.

Types only validation

Slower testsResultToleranceDifference with slowest
yup299 op/sec± 0.01 %
joi769 op/sec± 0.03 %+ 157.05 %
zod1 721 op/sec± 0.05 %+ 475.23 %
myzod5 460 op/sec± 0.05 %+ 1725.14 %
ajv70 548 op/sec± 0.32 %+ 23480.25 %
Types only validation

Comprehensive validation

Slower testsResultToleranceDifference with slowest
joi152 op/sec± 0.01 %
yup226 op/sec± 0.01 %+ 49.03 %
myzod469 op/sec± 0.02 %+ 209.19 %
zod970 op/sec± 0.03 %+ 539.62 %
ajv1988 op/sec± 0.04 %+ 1210.65 %
Comprehensive validation

Final conclusions

Benchmarks presented in library documentation can be conducted incorrectly, become out of date, or present only specific scenarios in which presented solution appear to be better than others. They should not be the only factor when it comes to choosing which solution to use in a project. Results mentioned in the myzod documentation are no longer valid. As of today (December 2023), myzod is only 3 to 4 times faster than zod when validating object structure only. When it comes to the actual validation, myzod (with validator) was slower than zod itself. These results suggest that zod got a lot faster over the last 3 years (results mentioned in myzod repo were added there in April 2020). In my opinion, picking the fastest option is not always a valid approach. Frequent updates, active community and developer experience are major factors, especially when developing a product that keeps evolving. When the development slows down, and product functionalities are considered stable, there comes the time for the performance optimizations. When it comes to choosing a validator library for the project, if it has to handle as much traffic as possible, I would recommend using Ajv. In other cases, Zod is my favorite solution because it works well with the Typescript ecosystem.

Photo by Sigmund on Unsplash

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