DuckDB for Spatial Data Exploration

DuckDB is a database management system for data analytics that has picked up steam in the recent months within the geospatial data community.

Chris Holmes documents his experiences with DuckDB and explores its potential for work with geospatial data:

I’m not the type who’s constantly jumping to new technologies and generally didn’t think that anything about a database could really impress me. But DuckDB somehow has become one of the pieces of technology – I gush about it to anyone who could possibly benefit.

There’s a lot to love about DuckDB: Its performance, its early support support for geospatial queries and data formats (although not fully mature), and smart extensions to SQL.

What sets it apart is DuckDB’s support for cloud-native operations via the httpfs extension and Parquet:

DuckDB also has the ability to work in a completely Cloud-Native Geospatial manner – you can treat remote files just like they’re on disk, and DuckDB will use range requests to optimize querying them.

In geospatial, we’re often dealing large data sets that are har to store and explore with traditional tools, unless you import the data into a database. But it’s not just going to make data access and processing easier on your computer. There’s also a great potential to move more large-data processing into the browser:

It’s not just that DuckDB is a great command-line and Python tool, but there’s also a brewing revolution with WASM, to run more and more powerful applications in the browser. DuckDB is easily run as WASM, so you can imagine a new class of analytic geospatial applications that are entirely in the browser.