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duckspatial

The {duckspatial} package provides fast and memory-efficient functions to analyze and manipulate large spatial vector datasets in R. It allows R users to benefit directly from the analytical power of DuckDB and its spatial extension, while remaining fully compatible with R’s spatial ecosystem, especially {sf}.

At its core, {duckspatial} bridges two worlds:

• R spatial workflows based on {sf} objects
• Database-backed spatial analytics powered by DuckDB SQL

This design makes {duckspatial} especially well suited for:

• Working with large spatial data sets
• Speeding up spatial analysis at scale
• Workflows where data does not fit comfortably in memory

Importantly, {duckspatial} brings the power of DuckDB spatial to R users while keeping workflows similar to {sf} .

Installation

You can install duckspatial directly from CRAN with:

install.packages("duckspatial")

Or you can install the development version from GitHub with:

# install.packages("pak")
pak::pak("Cidree/duckspatial")

Core idea: flexible spatial workflows

A central design principle of {duckspatial} is that the same spatial operation can be used in different ways, depending on how your data is stored and how you want to manage memory and performance.

Most functions in {duckspatial} support four complementary workflows:

1. Inputsf → Output sf
2. Input sf → Output DuckDB table
3. Input DuckDB table → Output sf
4. Input DuckDB table → Output DuckDB table

See the “Get Started” vignette for examples.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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