What is GIS?
If you stumbled upon this article, you’re most likely already familiar with the term GIS. But for the sake of clarity and in case we have some new people here, let’s define it.
Geographic Information System (GIS)
GIS is a technology used to create, manage, analyze, and map all types of data.
It allows us to visualize complicated datasets in a more digestible way. You can use GIS to find the best route, analyze potential locations for a new store, and much more.
What is Rust?
Rust is a systems programming language, meaning it can interact with low-level components of a computer. Think operating systems, drivers, and embedded systems. These types of languages, especially Rust, have low overhead and give you fine-grained control over memory.
When speed and performance matter, these languages shine. Other popular systems programming languages are C and C++. Rust, being the newest of the three, solves common problems that the others struggle with, such as memory safety, concurrency, and developer experience.
In 2019, Microsoft published an article stating that 70% of bugs in Windows were caused by memory safety issues. Rust eliminates entire categories of these bugs at compile time, offering a solid foundation for building fast and reliable code.
Why Rust’s Features Are Important for GIS
GIS inherently involves large datasets. Geography is big: the Earth spans 510 million square kilometers. Mapping a small town can involve millions of data points. Now scale that to states, countries, or continents, and datasets explode in size.
When dealing with large datasets, efficiency matters. Even a 1-millisecond improvement in processing time can reduce overall processing time dramatically, turning hours into minutes.
Speed is important, but so is reliability. You want to make sure your program is managing memory correctly. Runtime errors in large, complex systems are painful and costly to debug. Rust’s strengths, performance, safety, and concurrency, align perfectly with the demands of GIS work.
Rust vs Python
/* RUST CODE EXAMPLE */
use geos::{CoordSeq, Geom, Geometry};
use rand::prelude::*;
use std::time::Instant;
fn main() {
let mut rng = rand::thread_rng();
// Generate 10,000 random points
let points: Vec<Geometry> = (0..10_000)
.map(|_| {
let coords = CoordSeq::new_from_vec(&[&[
rng.gen_range(-180.0..180.0),
rng.gen_range(-90.0..90.0),
]])
.expect("failed to create CoordSeq");
Geometry::create_point(coords).expect("Failed to create point")
})
.collect();
let start = Instant::now();
// Buffer each point by 500 meters
let _buffers: Vec<Geometry> = points
.into_iter()
.map(|p| p.buffer(0.005, 8).expect("Failed to create buffer"))
.collect();
let duration = start.elapsed();
println!("Rust buffering time: {:.2?}", duration);
}
# PYTHON CODE EXAMPLE
from shapely.geometry import Point
import time
import random
# Generate 10,000 random points
points = [Point(random.uniform(-180, 180), random.uniform(-90, 90)) for _ in range(10000)]
start = time.time()
# Buffer each point by 500 meters (0.005 degrees approx, rough for lat/lon)
buffers = [p.buffer(0.005) for p in points]
end = time.time()
print(f"Python buffering time: {end - start:.2f} seconds")Rust: 0.11251 seconds
Python: 0.47 seconds
Both examples use libraries that tie into the same underlying geospatial library (GEOS). The big performance differences come from Python’s slower loop execution. Yes, Python is simpler and easier to read, which is why it’s so popular. But Rust isn’t to hard to read either, that is once you understand the basics.
A Look at Rust’s GIS Ecosystem
Rust’s GIS ecosystem is surprisingly strong. The GeoRust project provides a central place to discover geospatial libraries. Some highlights include:
- GeoZero: Zero-copy reading and writing of geospatial data (supports GeoParquet!)
- Geos: Rust bindings for GEOS (Geometry Engine Open Source)
- Proj: Bindings for the PROJ library (coordinate projection and transformation)
Also worth checking out is the free Geospatial Rust Book, which offers great walkthroughs for common GIS tasks in Rust.
What Rust is Missing
Rust’s biggest weakness in GIS is the lack of unified, high-level interfaces. Depending on your task, you may need to combine multiple libraries and handle much of the glue code yourself.
In contrast, Python’s geopandas abstracts many of these details. With a single import, you’re ready to manipulate spatial data, project coordinates, and plot results. Rust offers power and safety but still lacks the convenience layer many GIS analysts expect.
When to Use Rust Over Python (and Vice Versa)
Use Rust when:
- You need performance and memory efficiency
- You’re building production-grade systems or command-line tools
- You want compile-time guarantees to reduce runtime bugs
Use Python when:
- You need to prototype quickly or write small scripts
- You want easy access to mature geospatial tools
- You value simplicity and speed over raw performance
Both languages have their strengths. Rust isn’t here to replace Python, but it does offer a compelling option for GIS developers looking for speed, safety, and scalability.
Did you know GEO Jobe’s Software Services team offers custom app development?
Our team has decades of experience and success stories across multiple industries. While we are primarily focused on the Web GIS stack utilizing the ArcGIS® API for JavaScript, we also offer solutions such as custom python scripts/tools and custom ArcGIS® Pro addons. Ever wish you had access to ArcGIS® capabilities while using other software? We have proven success integrating ArcGIS® with other platforms, including Salesforce. Learn more about this service here, or email us at connect@geo-jobe.com!
Like this article? Explore these others from our MapThis! blog:
- ArcGIS Pro: Critical Considerations for Storing Your Data
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- UAV Mapping: Maximizing Accuracy with Ground Control Points
- 25 Years of GEO Jobe: Mapping a Legacy of Innovation & Community
- WATCH: Sharing Your ArcGIS Services Easier, Smarter, & More Securely
About Our Company
GEO Jobe is a leading GIS software and geospatial solutions provider, serving over 10,000 organizations globally. GEO Jobe is best known for developing the most popular applications in the ArcGIS Marketplace, including Admin Tools for ArcGIS, Backup My Org, Clean My Org and Scheduler for ArcGIS.
GEO Jobe offers U.S.-based 24/7 Support solutions for organizations using Esri’s ArcGIS© System. GEO Jobe also offers professional services focused on Esri’s ArcGIS© System, including custom software development, enterprise solution implementation, data science and UAV data collection.
Founded in 1999, GEO Jobe is in its 25th year of operation, has been an Esri business partner since 2002 and is currently a Platinum Partner.
