OxiGDAL 0.1.3 Released — Pure Rust GDAL Replacement for Cloud-Native Geospatial Workflows

The geospatial data foundation of the COOLJAPAN scientific computing ecosystem just went fully cloud-native and production-ready.

Today we released OxiGDAL 0.1.3 — a complete, production-grade pure Rust geospatial data abstraction library designed as a modern replacement for GDAL.

No C. No C++. No Fortran. No PROJ/GEOS system dependencies.
No build hell. No 1 GB+ Docker images.
Just clean, memory-safe, blazing-fast geospatial processing that compiles to a single static binary (or <1 MB WASM) and runs everywhere — from laptops to browsers to embedded devices to cloud clusters.

Why OxiGDAL 0.1.3 is a game changer

For decades, geospatial workflows meant depending on the massive GDAL C++ library (with its complex toolchain, PROJ, GEOS, and 1 GB+ Docker images).

These tools are powerful but suffer from:

• C/C++ memory unsafety and segfaults
• Heavy system dependencies and installation nightmares
• Poor WASM/embedded/cloud-native support
• Slow Python bindings (GeoPandas)
• Massive binaries and vendor lock-in

OxiGDAL 0.1.3 ends all of that.

It delivers competitive or superior performance while being 100% memory-safe and portable.
Notable results:

• GeoParquet vs GeoPandas: 10× faster
• COG tile access (local SSD): < 10 ms
• COG tile access (S3/GCS): < 100 ms
• GeoTIFF metadata reading: < 5 ms
• PROJ batch transform (1 M points): < 10 ms
• Docker image size: < 50 MB (vs 1 GB+ for GDAL)

Technical Deep Dive: How We Rebuilt GDAL in Pure Rust

The architecture uses 69 workspace crates organized into clean functional layers, radically optimized for modern Rust and cloud-native use:

1. Core & Algorithms (oxigdal-core, oxigdal-proj, oxigdal-algorithms)
   211+ embedded EPSG definitions, 20+ map projections (including Japan Plane Rectangular), SIMD-accelerated raster/vector ops (AVX-512/NEON).

2. Format Drivers (11 crates)
   GeoTIFF/COG, GeoJSON (RFC 7946), GeoParquet (Arrow-native), Zarr v2/v3, FlatGeobuf, Shapefile, NetCDF, HDF5, GRIB1/2, JPEG2000 (EBCOT decoder), VRT.

3. Cloud & Storage (oxigdal-cloud)
   Async S3/GCS/Azure Blob via HTTP range requests, pure-Rust compression (OxiARC integration), advanced caching.

4. GPU & Enterprise
   wgpu compute shaders, OGC WMS 1.3.0 / WFS 2.0.0 services, Raft HA clustering, Kafka/Kinesis streaming, AES-256-GCM security.

5. Bindings & CLI
   PyO3 (NumPy interop), WASM (<1 MB gzipped), Node.js, full CLI (oxigdal info, convert, warp, dem).

Key Rust advantages:

• Zero C/C++/Fortran dependencies in default features
• Fearless concurrency and guaranteed memory safety
• Pay-for-what-you-use modular features
• Trivial cross-compilation to WASM, iOS, Android, embedded no_std

What’s inside 0.1.3 (released March 17)

• Stability improvements and CI hardening
• Expanded EPSG coverage and JPEG2000 EBCOT tier-1 decoder
• Deeper OxiARC pure-Rust compression integration
• Enhanced cloud I/O and GPU shader performance
• Production readiness confirmed through 7,486 passing tests across 69 crates
• ~480,000 lines of pure Rust — zero warnings, clippy::unwrap_used = "deny"

This is the foundation

OxiGDAL is now the official geospatial backend for the entire COOLJAPAN scientific stack:

• SciRS2 / NumRS2 — all raster/vector and spatial algorithms
• OxiBLAS — accelerated linear algebra for terrain analysis
• OxiARC / OxiCode — cloud-native compression and serialization
• Spintronics / OxiHuman — geospatial integration for simulations and avatars
• OxiMedia / ToRSh — satellite imagery pipelines and RAG
• Future integration with OxiLean for formally verified CRS transformations

Repository: https://github.com/cool-japan/oxigdal

Star the repo if you want high-performance geospatial computing without the GDAL toolchain headaches.

The era of “just install GDAL and pray the C++ doesn’t segfault” is over.

Pure Rust cloud-native geospatial is here — fast, safe, and sovereign.

— KitaSan at COOLJAPAN OÜ March 17, 2026