Benchmark: JSON.Stringify / JSON.Parse vs TextEncoder / TextDecoder

Script Preparation code:

var i = 0;
var initialString = "This is the initial Test String";
var encoder = new TextEncoder();
var view = encoder.encode(initialString);
var initialObject = {someString: initialString};
var initialStringify = JSON.stringify(initialObject);

var decoder = new TextDecoder();

Tests:

Encode
var newString = "This is the updated Test String"; var view = encoder.encode(newString); if (i == 5000) console.log(view); i++;
EncodeInto
var newString = "This is the updated Test String"; var view = encoder.encodeInto(newString); if (i == 5000) console.log(view); i++;
JSON.Stringify
var newString = "This is the updated Test String"; var object = {someString: newString}; var stringify = JSON.stringify(object); if (i == 5000) console.log(stringify); i++;
Decode
var decoded = decoder.decode(view); if (i == 5000) console.log(decoded); i++;
JSON.Parse
var parse = JSON.parse(initialStringify) if (i == 5000) console.log(parse);

Historical Performance Data aggregated from 6 community runs

Desktop Results:

Chrome 6 runs

JSON.Parse

6.1M/s

JSON.Stringify

5.8M/s

Decode

3.4M/s

Encode

918K/s

EncodeInto

0/s

View exact numbers

✓ JSON.Parse: 6,068,602 ops/sec
• JSON.Stringify: 5,792,247 ops/sec
• Decode: 3,420,279 ops/sec
• Encode: 917,892 ops/sec
• EncodeInto: 0 ops/sec

Results show median performance across all community submissions. Run this benchmark yourself to verify on your device.

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Encode
EncodeInto
JSON.Stringify
Decode
JSON.Parse

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 10 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/141.0.0.0 Safari/537.36

Browser/OS: Chrome 141 on Mac OS X 10.15.7

View result in a separate tab

JSON.Stringify

11.8M/s

JSON.Parse

11.7M/s

Decode

11.7M/s

Encode

1.7M/s

EncodeInto

0/s

View exact numbers

Test name	Executions per second
✓ JSON.Stringify	11,786,870 Ops/sec
JSON.Parse	11,729,858 Ops/sec
Decode	11,705,654 Ops/sec
Encode	1,673,598 Ops/sec
EncodeInto	0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and its options.

**Benchmark Overview**

The benchmark measures the performance of different methods for converting between strings and JavaScript objects using `TextEncoder`/`TextDecoder`, as well as the traditional `JSON.stringify()`/`JSON.parse()` approach. The goal is to compare the execution speed of these methods on modern browsers (specifically, Chrome 126).

**Options Compared**

The benchmark compares five different options:

1. **Encode**: Encoding a string using `TextEncoder`.
2. **EncodeInto**: Encoding a string into a JavaScript object using `TextEncoder`.
3. **JSON.Stringify**: Converting a JavaScript object to a string using `JSON.stringify()`.
4. **Decode**: Decoding a `TextDecoder` buffer back into a string.
5. **JSON.Parse**: Parsing a string into a JavaScript object using `JSON.parse()`.

**Pros and Cons of Each Approach**

Here's a brief summary:

1. **Encode (TextEncoder)**:
	* Pros: Fast, efficient, and widely supported across browsers and platforms.
	* Cons: May not be suitable for large datasets or complex data structures.
2. **EncodeInto (TextEncoder)**:
	* Pros: Similar to Encode, but allows for more flexible encoding of strings into JavaScript objects.
	* Cons: May introduce additional overhead due to the need to create a buffer object.
3. **JSON.Stringify**:
	* Pros: Widely supported and easy to use, making it a popular choice for serialization purposes.
	* Cons: Can be slower than TextEncoder for large datasets or complex data structures.
4. **Decode (TextDecoder)**:
	* Pros: Fast and efficient, similar to Encode.
	* Cons: May not be suitable for large datasets or complex data structures.
5. **JSON.Parse**:
	* Pros: Widely supported and easy to use, making it a popular choice for deserialization purposes.
	* Cons: Can be slower than TextEncoder for large datasets or complex data structures.

**Library Used**

The benchmark uses `TextEncoder` and `TextDecoder`, which are part of the Web APIs specification. These libraries provide efficient and secure methods for encoding and decoding strings, as well as other binary data types.

**Special JS Feature/Syntax (None)**

There are no special JavaScript features or syntax used in this benchmark that would require specific knowledge to understand.

**Other Alternatives**

For those interested in exploring alternative approaches, here are a few options:

1. **Btoa()**: The browser-specific base64 encoding algorithm, which can be used for encoding strings.
2. **atob()**: The browser-specific base64 decoding algorithm, which can be used for decoding strings.
3. **URLSearchParams**: A DOM API for working with query strings and URL parameters.

Keep in mind that these alternatives may have different performance characteristics and usage scenarios compared to the methods tested in this benchmark.

JSON.Stringify / JSON.Parse vs TextEncoder / TextDecoder (version: 0) Benchmark.js

Comparing performance of: `Encode vs EncodeInto vs JSON.Stringify vs Decode vs JSON.Parse`

Created: 3 years ago by: Registered User

Go to the latest result

Encode

EncodeInto

JSON.Stringify

Decode

JSON.Parse

Historical Performance Data aggregated from 6 community runs

Desktop Results:

Chrome 6 runs

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

JSON.Stringify / JSON.Parse vs TextEncoder / TextDecoder (version: 0) Benchmark.js

Comparing performance of: Encode vs EncodeInto vs JSON.Stringify vs Decode vs JSON.Parse

Created: 3 years ago by: Registered User

Go to the latest result

Encode

EncodeInto

JSON.Stringify

Decode

JSON.Parse

Historical Performance Data aggregated from 6 community runs

Desktop Results:

Chrome 6 runs

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

Related benchmarks

Comparing performance of: `Encode vs EncodeInto vs JSON.Stringify vs Decode vs JSON.Parse`