Available Implementations
C++
Glaze — Production-ready library with unified JSON/BEVE API. SIMD-optimized, header-only, C++20. GitHub →
Rust
beve — Official implementation with zero-copy deserialization and Serde support. crates.io →
serde-beve — Serde integration for seamless use with Serde-compatible types. crates.io →
Python
load_beve.py — Pure Python reference implementation, no dependencies. GitHub →
MATLAB
load_beve.m / write_beve.m — Native MATLAB functions for reading and writing BEVE files. GitHub →
JavaScript / Go
Implementations in development. Check the repository →
Resources
Examples: Working code examples and sample data files in the repository.
Contributing: Follow the specification, include tests, and submit to GitHub discussions.
Performance Considerations
Use SIMD Where Possible
BEVE is designed for SIMD operations. Take advantage of vector instructions for array processing.
Zero-Copy Parsing
Implement zero-copy techniques when deserializing typed arrays for maximum performance.
Little Endian
Leverage native byte order on x86/ARM for fast integer operations.
Compression Integration
Consider integrating with LZ4, Zstandard, or Brotli for additional space savings.