What You Should Know About Spatial SQL


“Spatial SQL is a rising star in spatial analysis, and for good reason. Learn about the advantages of learning and using Spatial SQL here.”

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What You Should Know About Spatial SQL

Traditionally  spatial analysis has been behind the rest of the analytics world when it comes to features and capabilities. However  this is no longer the case due to the rise of spatial cloud computing using SQL. In recent years  the use of Spatial SQL has been growing across a variety of industries as more teams have begun to incorporate it into their modern GIS and geospatial stacks.

In this quick guide  we’ll cover:

  1. The definition of Spatial SQL
  3. How Spatial SQL differs from traditional SQL
  5. The advantages of using Spatial SQL for analysis  among others

A Brief Overview: What is Spatial SQL  and How is it Different from SQL?

Spatial SQL is a query language typically used by GIS analysts  data scientists and developers. Although Spatial SQL uses the same structure and elements of SQL  it has deeper capabilities that assist in a number of areas  like faster geospatial data processing and analysis and support spatial modeling and machine learning.  

Unlike the traditional version of this language  Spatial SQL enables users to work with geometry (feature shapes) and geography (feature locations) data types. It can help users analyze data types in the form of points  lines and polygons; and the geospatial data types analyzed can include addresses  place names  latitude and longitude coordinates  countries  states  roads  etc.

Additionally  as well as using internally first-party (think CRM  loyalty card and e-commerce sales) data  organizations can also take advantage of open data streams from spatial data catalogs to further enrich their analysis – the publicly available premium spatial data themes being used more frequently include financial  road traffic  human mobility and climate  among others.

What Are the Benefits of Spatial SQL?

SQL in itself is a highly beneficial tool to manage large geographic databases. However  Spatial SQL provides numerous additional advantages that take spatial analysis to the next level. If you find yourself asking “why should I use Spatial SQL?” or “is Spatial SQL valuable to learn?” just know that when utilizing this form of the common programming language  individuals can…

  • Experience more efficiency in analytics workflows and task management
  • Work with Big Data in SQL-enabled databases (like PostgreSQL with PostGIS  Microsoft SQL Server  MySQL  Oracle Spatial) and cloud data warehouses (such as Google BigQuery  Databricks  Snowflake and Redshift)  but also better manage and analyze data in more “traditional” geospatial formats such as CSVs and shapefiles
  • Steer clear of silos by supporting cross-functional collaboration between teams conducting spatial analysis and teams performing non-spatial analysis  providing confidence that everyone is working from a single-source-of-truth database
  • Find more opportunities for repeatability both inside and outside of an organization
  • Open up accessibility for the wider analytics community that may specialize in less technical departments  such as business intelligence or operations
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Who Can Use Spatial SQL?

At the end of the day  anyone can learn – and start programming in – Spatial SQL. Its concepts  syntax and formatting are logical and easy to remember. Nevertheless  Spatial SQL is typically the best fit for data scientists  spatial data scientists  GIS users  developers  analysts and teams who work with data in SQL-based databases or warehouses.

As adoption of this language continues to grow  there has been a rise in Spatial SQL use by titles associated with less technical roles like marketing  business intelligence and operations.

Spatial SQL User Examples

A GIS analyst may use data stored in a Spatial SQL database for querying  analysis and visualization. The analyst could use these datasets to gain insights using spatial relationship functions in Spatial SQL and other tools. They then access and visualize the data and analysis  through the use of tools like QGIS  CARTO or Python.

screenshot of CARTO builder map using spatial sql editor

A marketing or general business user  on the other hand  may access this data without realizing what it is. They may review data that was generated by spatial data scientists from Spatial SQL databases in reports  maps and business intelligence tools  which will enable them to create  access and interpret insights more accurately.

Is it Hard to Learn Spatial SQL?

Although there may be a bit of a curve when it comes to learning Spatial SQL (especially if you haven’t used SQL previously) if you’re switching from another language like Python  the return on investment makes up for the effort. Also  users of “point-and-click” GIS platforms will typically have an understanding of basic SQL syntax and operators through creating definition  label and symbology queries. This will make the transition to more complex Spatial SQL processing a smaller jump since those with this background wouldn’t be starting entirely from scratch.

How Do I Get Started?

With more and more organizations looking to utilize this tool to conduct spatial analysis  the number of resources are only growing for folks looking to get started with Spatial SQL. From webinars and podcasts to tutorials and articles  there are plenty of online resources available for beginners and advanced users alike. You can view a helpful list of Spatial SQL learning resources here.

What Does the Future Hold for Spatial SQL?


image encouraging readers to download the state of spatial sql report by CARTO

Curious about the state of Spatial SQL use in GIS and what the future holds? Want to dive deeper into the benefits of learning this language? We’ve got you covered! In order to have a better understanding of the impact of Spatial SQL in GIS  as well as its advantages and unique use cases  we surveyed over 200 professionals using spatial analysis from organizations across the world in the State of Spatial SQL Survey 2022.

Read about new insights  including what to expect as adoption continues to gain momentum  in CARTO’s State of Spatial SQL report. Download it here.


EU Flag This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 960401.