SedonaDB: A new geospatial DataFrame library written in Rust
a day ago
- #geospatial
- #database
- #analytics
- SedonaDB is an open-source, single-node analytical database engine with native geospatial support.
- Built in Rust, SedonaDB is lightweight, fast, and integrates with Apache Arrow and DataFusion.
- Provides full support for spatial types, joins, CRS, and functions with Python, SQL, R, and Rust APIs.
- Includes query optimizations, indexing, and data pruning for high-performance spatial operations.
- Seamlessly integrates with GeoArrow, GeoParquet, and GeoPandas, with future raster data support planned.
- Features CRS management for safer pipelines, automatically tracking CRS in files and DataFrames.
- Benchmarked via Apache Sedona SpatialBench, showing balanced performance across spatial queries.
- SedonaDB is optimized for small-to-medium datasets, complementing SedonaSpark for large-scale workloads.
- Future roadmap includes more ST functions, additional spatial file formats, and raster support.
- Community contributions are welcome via Discord, GitHub, and regular contributor meetings.