Introduction

Modern geospatial workflows demand efficient data formats and visualization tools. This tutorial explores three complementary technologies that revolutionize how we handle and visualize large spatial datasets: GeoParquet, GeoArrow, and Deck.GL.

What Are They?

GeoParquet 🗄️

GeoParquet is a columnar storage format for geospatial data, built on Apache Parquet. It stores geometry data alongside attributes in a highly compressed, cloud-optimized format.

Key Features:

• Columnar storage for efficient queries
• Built-in compression (typically 10-50x smaller than GeoJSON)
• Cloud-native with partial reading support
• Preserves spatial metadata and CRS information

📚 Official Documentation: geoparquet.org

GeoArrow 🚀

GeoArrow is an in-memory columnar format for geospatial data, extending Apache Arrow. It provides a standardized way to represent geometries in memory for ultra-fast processing.

Key Features:

• Zero-copy data sharing between tools
• Vectorized operations for high performance
• Language-agnostic memory layout
• Perfect for data pipelines and analysis

📚 Official Documentation: geoarrow.org

Deck.GL 🎨