CARTO is a cloud-native spatial analytics platform, while PostGIS is an open-source spatial extension for PostgreSQL. Both enable spatial SQL queries, but they differ fundamentally in architecture, scalability, and management approach.
CARTO vs PostGIS at a Glance
| Feature | CARTO | PostGIS |
|---|---|---|
| Architecture | Cloud-native, runs inside data warehouses | PostgreSQL extension, self-managed |
| Infrastructure | Fully managed, no servers to maintain | Requires PostgreSQL admin and server management |
| Scalability | Automatic, leverages cloud warehouse compute | Limited by single PostgreSQL instance |
| Data warehouses | BigQuery, Snowflake, Databricks, Redshift | PostgreSQL only |
| Spatial SQL | Analytics Toolbox with 100+ functions | Comprehensive ST_ functions |
| Visualization | Built-in Builder, deck.gl, dynamic tiling | Requires separate visualization tools |
| Spatial indexes | Native H3, Quadbin, S2 support | R-tree, GiST indexes |
| AI Agents | Built-in Agentic GIS with MCP support | Not available |
| Data catalog | 12,000+ datasets via Data Observatory | No built-in data catalog |
| Collaboration | Multi-user workspace with sharing | Database-level access control |
| Cost model | Subscription, pay for what you use | Free software, but infrastructure costs |
| License | Commercial | Open source (GPL) |
When to Choose CARTO Over PostGIS
You should consider CARTO when:
- Your data already lives in a cloud data warehouse (BigQuery, Snowflake, Databricks)
- You need to scale spatial queries to billions of rows without managing infrastructure
- You want built-in visualization, sharing, and collaboration tools
- Your team includes analysts who need spatial capabilities without database administration skills
- You need AI-powered spatial analysis with natural language interfaces
- You want access to enrichment data (demographics, POIs, mobility data)
When PostGIS May Be the Right Choice
PostGIS may be better when:
- You need a free, fully open-source solution
- Your team has strong PostgreSQL expertise and existing infrastructure
- Your datasets are small to medium (millions, not billions of rows)
- You need maximum control over database configuration and tuning
- You’re building applications that require transactional spatial operations (OLTP)
Key Differences Explained
Cloud-Native vs Self-Managed
PostGIS runs as an extension within a PostgreSQL database. This means you manage the server, handle backups, configure replication, and plan capacity. CARTO runs natively inside cloud data warehouses, leveraging their built-in scaling, security, and management capabilities.
Scalability
PostGIS performance is bounded by the resources of a single PostgreSQL instance (or a carefully configured cluster). CARTO leverages the distributed compute of cloud data warehouses — the same query engine that powers BigQuery or Snowflake processes spatial operations, automatically parallelizing across available resources.
Spatial SQL Compatibility
Both CARTO and PostGIS support the OGC Simple Features standard. PostGIS implements the ST_ function family comprehensively. CARTO’s Analytics Toolbox provides equivalent functions plus additional capabilities like spatial indexing (H3, Quadbin, S2), spatial statistics (Moran’s I, Getis-Ord), and geocoding — all running natively in SQL.
Visualization and Sharing
PostGIS is a database extension — it has no built-in visualization. You need additional tools (QGIS, Leaflet, Mapbox) to see your data on a map. CARTO includes Builder (a no-code map builder), deck.gl-powered dynamic tiling for billions of features, and sharing capabilities for distributing maps and dashboards across an organization.
Migrating from PostGIS to CARTO
Many organizations start with PostGIS and migrate to CARTO as their spatial analytics needs grow beyond what a single PostgreSQL instance can handle. The migration typically involves:
- Moving spatial data to a cloud data warehouse (BigQuery, Snowflake, or Databricks)
- Translating PostGIS SQL queries to equivalent Analytics Toolbox functions
- Building visualizations and dashboards in CARTO Builder
Since both platforms use standard spatial SQL, query migration is often straightforward — most ST_ functions have direct equivalents in CARTO’s Analytics Toolbox.