11-19, 14:30–14:55 (Pacific/Auckland), WG403
DuckDB, GDAL, and libraries like Lonboard can now efficiently share large vector data at low cost, thanks to GeoArrow. This talk will explain what GeoArrow is and how to get the best performance when sharing data between these libraries with practical examples.
DuckDB, GDAL, libraries like Lonboard, and more can now efficiently share large vector data at low cost, thanks to GeoArrow, a binary representation for vector geometries that can be shared across libraries without any data copies.
GeoArrow is a relatively low-level technology that tends to be unseen by end-users. This is great! Users just see performance improvements!
For example, GDAL 3.6 introduced support for exposing the data read by OGR’s vector drivers as GeoArrow. This dramatically improved performance: reading from FlatGeobuf or GeoPackage files to a GeoPandas GeoDataFrame improved by 20x.
But it can be useful to understand the factors behind what makes GeoArrow so performant. This talk will explain what GeoArrow is, how it differs from other new technologies like GeoParquet, and how to get the best performance when sharing data between these libraries with practical examples. It will also give a quick peek under the hood for how advanced users can create a cross-language library from C or Rust, but this talk will aim to be digestible for wide audiences; no deep technical prerequisites are expected.
Kyle is a cloud engineer at Development Seed. He builds open source tools and infrastructure that process and visualize geospatial data. Kyle is particularly excited about cloud-native vector data formats, speeding up Python and JavaScript applications from Rust, spatial indexes, and efficient data pipelines.
Before joining Development Seed, Kyle previously worked as a software engineer at Unfolded and then Foursquare, building geospatial data visualizations on the web for vector and raster data.
Based in New York City, Kyle spends time running in Central Park, exploring the city, and dodging tourists. Kyle is a graduate of University of California, Los Angeles where he received a B.A. in Economics with a minor in Mathematics.