2026-11-03 –, Tofanelli
The Python and R bindings for SedonaDB were purpose-built to accelerate performance-critical spatial analyses or scale existing analyses alongside existing free and open source tools.
Whereas Python and R users have long had access to spatial databases via SQL-based APIs (e.g., PostGIS, DuckDB), the spatial capabilities of databases are rarely exposed via bindings in a way that leverages features of the Python/R editors (e.g., autocomplete, inline documentation) to improve the experience of writing code against a spatial database. In September, 2025, the Apache Sedona community released SedonaDB, a purpose-built engine based on DataFusion. The project consists of (1) purpose-built extensions that map spatial concepts to relational database concepts that can be optimized and executed in parallel by the underlying DataFusion engine, (2) a purpose-built Python interface that handles spatial Python objects and is specifically designed to interoperate with existing Python-based spatial workflows, and (3) R bindings that allow SedonaDB to interoperate with the sf, wk, and geoarrow packages. Since its initial release we have built SedonaDB into a fully-featured spatial engine including support for GDAL read/write, larger-than memory spatial joins, cloud-native format support, a fully featured geography data type, and over 170 spatial functions with high PostGIS compatibility. Collectively, we hope to demonstrate how SedonaDB for R and Python can be used alongside existing free and open source tools to make spatial analyses faster and more fun to write.
Jia Yu is a co-founder of Wherobots, a Spatial Intelligence Cloud platform for spatial data ETL, analytics, and AI. Previously, he was a Tenure-Track Assistant Professor of Computer Science at Washington State University (2020–2023) and earned his Ph.D. from Arizona State University. Jia specializes in large-scale database systems and geospatial data management, with a focus on distributed systems, indexing, and visualization. His work has been featured in top conferences and journals such as SIGMOD, VLDB, ICDE, SIGSPATIAL, and VLDB Journal. He is the primary contributor to Apache Sedona, an open-source big spatial data framework with over 2 million monthly downloads and widespread industry adoption.
Dewey Dunnington (Ph.D., P.Geo.) is a software engineer and geoscientist based in Winnipeg, Manitoba. As a software engineer he works on scaling spatial data science using Apache Sedona and Apache Arrow at Wherobots. Dewey is a co-creator of GeoArrow, nanoarrow, and a contributor to the Arrow Database Connectivity (ADBC) project. As a geoscientist, he has worked in contaminated site remediation, taught Applied Geomorphology, and has authored more than a dozen articles on lake water and sediment geochemistry. Dewey is an Apache Arrow and Apache Sedona Project Management Committee member, an RStudio-certified tidyverse instructor, an NSERC Postgraduate Scholarship (Doctoral) recipient, and maintainer of dozens of R, Python, C, and C++ libraries at the intersection of geoscience, geospatial data, and enterprise data connectivity.