Dewey Dunnington - Introducing nanoarrow: the world's tiniest Arrow Implementation | SciPy 2024

NanoArrow is a minimal Arrow implementation designed for efficient data transfer between different languages and systems, using only two core files

Key advantages of NanoArrow include:

• Very small footprint compared to full Arrow C++ implementation
• No complex dependencies
• Efficient handling of strings and null values
• Easy integration into C libraries

Primary use cases:

• Wrapping C libraries that need Arrow functionality
• Fast data transfer between different languages/runtimes
• Efficient handling of large string arrays
• Testing and development of Arrow-based functionality

NanoArrow handles data representation through:

• Separate buffers for nullability
• Efficient string encoding
• Buffer protocol compatibility in Python
• Support for Arrow IPC format

Compared to full Arrow implementation:

• More limited in scope (no nested data structures)
• Focuses on core data transfer functionality
• Lighter weight alternative for basic Arrow needs
• Better suited for embedded systems or minimal dependencies

Successfully used in projects like:

• Snowflake Python connector
• GeoArrow implementations
• Testing frameworks
• Language bindings for C libraries

Particularly valuable when:

• Working with cross-language data transfer
• Dealing with large string datasets
• Need for minimal dependency overhead
• Building Arrow-compatible interfaces