Why JSONL is the Standard for Large Datasets

As data grows, standard formats like CSV and JSON start to show their cracks. CSV struggles with nested data, and standard JSON becomes a memory hog. Enter JSONL.

The Problem with Big JSON

Imagine a 10GB JSON file. To read the last record, a parser typically needs to read the opening bracket [, parse every single object, and wait for the closing bracket ]. If the syntax is broken anywhere in the middle, the whole file might be unreadable.

The JSONL Solution

With JSON Lines, every line is independent. If line 500 is corrupt, you can skip it and read line 501. This robustness makes it the de facto standard for:

• Application Logs: Structured logging often outputs one JSON object per event.
• Data Lakes: Storing raw data in S3/GCS.
• AI Training: Streaming millions of examples to a GPU cluster.

Need to convert your legacy data? Use our converter.