Convert XLSX to Arrow

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

1
Pick Your XLSX 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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XLSX

XLSX files are Excel files that use the Office Open XML format, which Microsoft introduced with Excel 2007.

Like XLS files, XLSX files can have multiple sheets, and each sheet can contain multiple rows and columns of data. They offer several advantages over the older XLS format.

Key features of XLSX files include:

  • Better compression, resulting in smaller file sizes
  • Enhanced security features, including password protection and digital signatures
  • Better recovery from file corruption
  • Support for more rows (1,048,576) and columns (16,384) per sheet
  • Works with a wide range of applications and programming languages

XLSX files are based on XML and ZIP technologies, making them easier for third-party software to read and write.

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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