How Good Are Modern Spatial Libraries?

Varun Pandey,Andreas Kipf,Alfons Kemper,Alexander van Renen

doi:10.1007/s41019-020-00147-9

Abstract

Many applications today like Uber, Yelp, Tinder, etc. rely on spatial data or locations from its users. These applications and services either build their own spatial data management systems or rely on existing solutions. JTS Topology Suite (JTS), its C++ port GEOS, Google S2, ESRI Geometry API, and Java Spatial Index (JSI) are some of the spatial processing libraries that these systems build upon. These applications and services depend on indexing capabilities available in these libraries for high-performance spatial query processing. In this work, we compare these libraries qualitatively and quantitatively based on four different spatial queries using two real world datasets. We also compare these libraries with an open-source implementation of the Vantage Point Tree—an index structure that has been well studied in image retrieval and nearest-neighbor search algorithms for high-dimensional data. We found that Vantage Point Trees are very competitive and even outperform the aforementioned libraries in two queries.

Highlights

In recent years, services such as recommending close-by social events, businesses, or restaurants as well as navigation, location-based mobile advertising, and social media platforms have fueled an exponential growth in location-enabled data
Spherical geometry is generally considered better suited to work with geographic data on a global scale
ESRI Quadtree has to be tuned for the dataset that it indexes, and memory management in Geometry Engine Open Source (GEOS) could be improved

Summary

Introduction

Services such as recommending close-by social events, businesses, or restaurants as well as navigation, location-based mobile advertising, and social media platforms have fueled an exponential growth in location-enabled data. The unprecedented rise of location-based services has led to a considerable amount of research efforts that have been focused on four broad areas; (1) systems that scale out [2–4, 9, USA. Some of the most popular spatial libraries are: JTS Topology Suite (JTS), its C++ port Geometry Engine Open Source (GEOS), Google S2 (S2), ESRI Geometry API, and Java Spatial Index (JSI). Today, these libraries are being used in a variety of services and research projects alike. To make planar geometries work with geographic data, Earth has to be projected onto a plane. Spherical geometry is generally considered better suited to work with geographic data on a global scale

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