Convert JSON to Arrow

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

1
Pick Your JSON 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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JSON

JSON (JavaScript Object Notation) is a lightweight data format that's easy for humans to read and write, and easy for machines to parse and generate.

Originally created for JavaScript, JSON quickly became the go-to format for web data exchange because it's simple and versatile. Now it's used across many programming languages and platforms.

JSON is a staple in web applications. It can represent structured data from simple key-value pairs to complex nested objects and arrays, making it perfect for client-server communication.

Schema

JSON's flexible structure is great, but it can make data integrity and processing tricky, especially with large or complex datasets.

Konbert automatically figures out the schema of your JSON data. We scan your JSON file to identify its structure, making sure all data is accurately captured and maintained throughout the conversion process. This preserves the integrity of your information.

Character encoding

According to RFC 8259, strings in uploaded JSON files should be encoded in UTF-8.

If your file has non UTF-8 characters, you might run into errors when parsing your data.

Nested data

We can read and flatten nested objects and arrays if you want to convert them to flat data like CSV or Excel.

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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