JSON vs JSONL: Understanding JSON Lines Format

If you work with JSON data, you might have come across JSONL (also called JSON Lines or NDJSON). While they look similar, they're actually quite different in how they structure data. Understanding the difference between JSON and JSONL can save you a lot of headaches when processing large datasets or streaming data.

In this guide, we'll break down what makes JSONL different from regular JSON, when you should use each format, and how they handle different use cases. Whether you're working with log files, streaming data, or just curious about different JSON formats, this article will help you understand which one fits your needs.

Need to work with JSON and JSONL? Try our JSON formatter,JSON validator,JSON to JSONL, orJSONL to JSON converter tools.

What is JSONL (JSON Lines)?

JSONL (JSON Lines) is a format where each line is a valid JSON object, and lines are separated by newline characters. Think of it as a text file where every single line contains one complete JSON object. It's also known as NDJSON (Newline Delimited JSON) or JSON streaming format.

The beauty of JSONL is its simplicity: you can process one line at a time without loading the entire file into memory. This makes it perfect for handling huge datasets, log files, or streaming data where you don't want to wait for everything to load before you start processing.

Side-by-Side Comparison

Let's see the same data represented in both formats. Here's a list of user records:

[
  {
    "name": "Alice",
    "age": 30,
    "city": "New York"
  },
  {
    "name": "Bob",
    "age": 25,
    "city": "London"
  },
  {
    "name": "Charlie",
    "age": 35,
    "city": "Tokyo"
  }
]

{"name":"Alice","age":30,"city":"New York"}
{"name":"Bob","age":25,"city":"London"}
{"name":"Charlie","age":35,"city":"Tokyo"}

Key Differences

Complete Comparison Table

When to Use Each Format

Working with JSONL in Code

Here's how you can read and write JSONL files in different programming languages:

import json

# Reading JSONL file
with open('data.jsonl', 'r') as f:
    for line in f:
        obj = json.loads(line)
        print(obj)

# Writing JSONL file
data = [
    {"name": "Alice", "age": 30},
    {"name": "Bob", "age": 25}
]

with open('output.jsonl', 'w') as f:
    for obj in data:
        f.write(json.dumps(obj) + '\n')

const fs = require('fs');
const readline = require('readline');

// Reading JSONL file
const rl = readline.createInterface({
  input: fs.createReadStream('data.jsonl')
});

rl.on('line', (line) => {
  const obj = JSON.parse(line);
  console.log(obj);
});

// Writing JSONL file
const data = [
  {name: 'Alice', age: 30},
  {name: 'Bob', age: 25}
];

const output = data.map(obj => JSON.stringify(obj)).join('\n');
fs.writeFileSync('output.jsonl', output);

Real-World Use Cases

Converting Between JSON and JSONL

Sometimes you need to convert between the two formats. Here's how:

# Python
import json

with open('data.json', 'r') as f:
    array = json.load(f)

with open('data.jsonl', 'w') as f:
    for item in array:
        f.write(json.dumps(item) + '\n')

# Python
import json

array = []
with open('data.jsonl', 'r') as f:
    for line in f:
        array.append(json.loads(line))

with open('data.json', 'w') as f:
    json.dump(array, f, indent=2)

Helpful JSON Tools

Final Thoughts

JSON and JSONL aren't competing formats – they're tools for different jobs. Regular JSON is great when you need a structured document that's easy to read and work with in most programming environments. JSONL shines when you're dealing with large volumes of data, streaming scenarios, or situations where you need to process records independently.

Think of JSON as a book – everything is organized together in one complete structure. JSONL is more like a stack of index cards – each card is independent, and you can add, remove, or process them one at a time without touching the others.