Convert NDJSON to Arrow

Upload your NDJSON file to convert to Arrow - paste a link or drag and drop. Free for files up to 5MB, no account needed.

1
Pick Your NDJSON File
You can upload files from your computer or import from a URL.
2
Preview and Configure
Preview your file and configure the conversion options if needed.
3
Convert and Download
Click "Convert" to transform your file into Arrow and download it instantly.
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NDJSON

NDJSON (Newline Delimited JSON) is a handy format for storing or streaming structured data that you can process one record at a time. Each line in an NDJSON file is a valid JSON object, with a newline character separating them.

This format works great for handling large datasets. You can easily parse and process data line by line without loading the entire file into memory.

Key Features

  • Each line is a complete JSON object
  • Easy to read and write sequentially
  • Great for streaming and logging
  • Allows partial processing of large datasets

NDJSON is popular in data pipelines, log processing, and situations where you need to add new data to existing files without changing the whole structure.

Arrow

Apache Arrow is a cross-language platform for in-memory data. It defines a standard columnar memory format for flat and hierarchical data that works across different programming languages. This format is optimized for efficient analytics on modern hardware like CPUs and GPUs.

Arrow can handle complex nested data structures and lets you query and work with specific columns without reading the entire dataset.

Key Features

  • Columnar memory format for flat and hierarchical data
  • Works with any programming language
  • Optimized for analytics and modern hardware
  • Supports complex nested data structures
  • Enables efficient zero-copy reads

Use Cases

Apache Arrow shines in scenarios like:

  • Big data processing and analytics
  • Machine learning and AI pipelines
  • Data exchange between different systems and languages
  • High-performance computing applications

Its efficient memory layout and standardized format make it a great choice for applications that need fast data processing and compatibility between different tools and languages.

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