Geospatial Analytics & AWS: CARTO's Spatial Analytics in Redshift

Summary

We are excited to announce CARTO's Spatial Analytics in Redshift. Discover how to leverage the geospatial capabilities of Redshift & sign up for a free trial today!

This post may describe functionality for an old version of CARTO. Find out about the latest and cloud-native version here.
Geospatial Analytics & AWS: CARTO's Spatial Analytics in Redshift

As we continue in our mission to help our customers unlock spatial analytics in the cloud  today we are excited to announce the general availability of CARTO's Spatial Analytics in Redshift.

Amazon Redshift is the most widely used cloud data warehouse and forms part of the larger cloud computing platform Amazon Web Services. It’s a fully managed  petabyte-scale cloud-based data warehouse product designed for large-scale dataset storage and analysis  providing unparalleled agility  flexibility  and cost-effectiveness.

In 2019  Amazon Redshift added spatial support  making it possible to utilize Amazon Redshift as a complete spatial database engine. Since then many upgrades have been implemented with GEOGRAPHY support and speed acceleration among other things.

Building on this support, the team at CARTO have worked to extend the geospatial capabilities  of the Redshift platform enabling organizations to visualize SQL results  make maps  build reports  perform spatial analysis  join third party location data  develop spatial applications  and much more. For more details on our collaboration with Redshift  check out our guest post on the AWS blog.  

The CARTO Spatial Extension for Redshift

Screenshots of CARTO Spatial Extension for Redshift

Today’s CARTO's Spatial Analytics in Redshift announcement is made possible following a complete redevelopment of our platform. Our all-new cloud native platform gives Redshift users unprecedented flexibility to:

  • Visually explore and manage spatial data in almost any format.
  • Import geospatial files supporting formats such as geojson, kml, geopackages.
  • Create stunning maps with large amounts of data using SQL and share them.
  • Perform advanced spatial analysis using a complete toolbox of spatial UDFs.
  • Get access to thousands of spatial datasets such as demographics or financial data to enrich your data.
  • Develop insight driven web applications visualizing data from Redshift into Amazon Location maps.

Connect & explore data on your Amazon Redshift cluster

Within the brand new CARTO Workspace a new connection to Redshift can be made with ease. To quickly preview spatial data, CARTO detects if there is a GEOGRAPHY field within any selected table and provides you with a map preview along with other information.

Screenshot of Data Explorer

Amazon Redshift allows you to import shapefiles stored in S3 by using a COPY command. To speed up this process CARTO now allows you to simply drag and drop multiple spatial files  such as geojson  csv with WKT or WKB  and many more formats coming soon.

Creating maps using SQL

Our Builder tool has been completely redesigned and allows sources to be set as a table or defined as a SQL. When using SQL  you can enter any SQL that returns a GEOMETRY to visualize on the map which is then updated in real-time as further iterations are made. Queries are executed live in Amazon Redshift and return the results in a format optimized for handling large datasets.

Builder gives you the possibility to apply filters on the client side to further analyze the dataset  add widgets  change tooltips or the base map. Maps can be shared publicly or with members of your organization and are fully backed by CDN with the data continually updated from the Amazon Redshift source.

Screenshot showing Builder interface

Introducing the Analytics Toolbox for Redshift

Diagram showing the components of the Analytics Toolbox


For both Developers and Data Scientists, our Analytics Toolbox brings 46 advanced spatial functions that can be deployed inside Redshift complementing those already built in and providing further capabilities that bring it closer to what PostGIS provides and more.

For more details on how to set up the Analytics Toolbox refer to this guide.

Thousands of spatial datasets to enrich your analysis

At the heart of our platform is the Data Observatory  making access to spatial datasets as frictionless as possible. Through the Spatial Extension for Redshift users can browse  visualize  and ingest thousands of curated spatial datasets, including Demographics, Points of Interest, Mobility, Environmental, Financial, Behavioral data  and more.

A lot of these datasets are now available directly through the AWS Data Exchange with future plans to enable additional access through Redshift Spectrum so users never have to worry about not having the latest data available or setting up complex ETLs.

Develop web apps visualizing Redshift data with CARTO & Amazon Location

CARTO utilizes the Open Source library deck.gl which exposes a CARTOLayer that takes care of retrieving data from Redshift and lets you design your web apps visually.

The two principal ingredients for designing a web app with a map are the basemap layer and data layer. The data layer comes from either SQL or a table in Redshift  and for the basemap you can use the service from Amazon Location or any other supported platform.

Spatial Analysis in Redshift

With the geospatial capabilities enabled in Amazon Redshift and the tools from CARTO it is now possible to solve a wide range of spatial use cases natively in the cloud. Users love the fact that they don't have to move data out of Redshift into other systems  making the most of its scalability and security.


And thinking even bigger, AWS provides a great foundation for a Geospatial Cloud, with services like Earth on AWS, AWS Data Exchange, Amazon Athena  and much more. With CARTO's Spatial Analytics in Redshift we have the components to make this vision a reality.

This platform is available as a free 14 day trial. Click here to sign up and get access to all of these great  new features.

 

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