The CARTO Analytics Toolbox is a set of UDFs and Stored Procedures to unlock Spatial Analytics. It is organized into modules based on the functionality they offer. This toolbox is cloud-native, which means it is available for different data warehouses: BigQuery, Snowflake, Redshift, Postgres, and Databricks. It is built on top of the data warehouse's GIS features, extending and complementing this functionality.

BigQuery	Snowflake	Redshift	Postgres	Databricks

This repo contains the core open-source modules of the toolbox. CARTO offers a set of premium modules that are available for CARTO users.

The Analytics Toolbox has two parallel components:

1. Gateway (gateway/): Lambda-based Python functions deployed to AWS Lambda

   • All deployment logic in gateway/logic/
   • Open-source functions in gateway/functions/

2. Clouds (clouds/{cloud}/): Native SQL UDFs specific to each cloud platform

   • BigQuery, Snowflake, Redshift, Postgres, Databricks

Using the functions on this project depends on the Datawarehouse you are using. In BigQuery and Snowflake you can access them directly as a shared resources without having to install them, for the rest you will have to install them locally on your database.

You can use the functions directly as they're globally shared in the US region:

SELECT `carto-os.carto.H3_CENTER`('84390cbffffffff')

If you need to use them from the Europe region use:

SELECT `carto-os-eu.carto.H3_CENTER`('84390cbffffffff')

If you need to install them in your own VPC or a different region, see the cloud-specific documentation below.

The easiest way to start using these functions is to add them to your Datawarehouse through the Snowflake Marketplace. Go there and install it using the regular methods. After that you should be able to use them on the location you have installed them. For example try:

SELECT carto_os.carto.H3_FROMGEOGPOINT(ST_POINT(-3.7038, 40.4168), 4)

If you need to install them directly, not through the data share process, follow the instructions later on.

Right now the only way to get access the Analytics toolbox is by installing it directly on your database. Follow the instructions later on.

For developing and deploying Lambda-based Python functions:

Documentation:

• gateway/README.md - User-friendly guide for creating functions
• CLAUDE.md - Complete technical documentation

Quick Start:

cd gateway

# Setup
make venv
cp .env.template .env
# Edit .env with your credentials

# Build and test
make build cloud=redshift
make test-unit cloud=redshift

# Deploy
make deploy cloud=redshift

All deployment logic lives in gateway/logic/:

• logic/common/engine/ - Catalog, validators, packagers
• logic/clouds/redshift/ - Redshift CLI and SQL generation
• logic/platforms/aws-lambda/ - Lambda deployment

For cloud-specific native SQL UDFs, see the cloud-specific READMEs:

Gateway functions:

cd gateway

# Build functions (required before testing)
make build cloud=redshift

# Run tests
make test-unit cloud=redshift
make test-integration cloud=redshift

# Deploy
make deploy cloud=redshift

# Lint
make lint
make lint-fix

# Create distribution package
make create-package cloud=redshift

Cloud functions:

Switch to a specific cloud directory (e.g., cd clouds/snowflake):

# All tests
make test

# Specific module(s)
make test modules=h3
make test modules=h3,transformations

# Specific function(s)
make test functions=H3_POLYFILL
make test functions=H3_POLYFILL,ST_BUFFER

# Deploy
make deploy

This project is open source. We're happy to receive feedback and contributions! Feel free to:

• Open a ticket with a bug report, question, or discussion
• Submit a pull request with a fix or new feature

For technical details and architecture, see CLAUDE.md.