PostGIS Connections
Aurora provides direct integration with PostGIS databases through two connection modes:
Import ? ingest PostGIS data into Aurora datasets
Remote ? use PostGIS data live without ingestion
These options allow Aurora to support both managed datasets and live database sources.
Overview
PostGIS connections allow Aurora to access spatial tables from external PostgreSQL/PostGIS databases.
Users can choose between:
Copying data into Aurora (Import)
Referencing data in place (Remote)
This enables flexible integration with enterprise GIS databases.
Connection Modes
Aurora supports two PostGIS connection modes.
PostGIS Import
Import copies spatial tables from PostGIS into Aurora datasets.
Imported datasets behave like native Aurora data and can be used in:
Maps
Dashboards
Pipelines
Analysis
Apps
Import supports:
One-time import
Scheduled refresh
This is equivalent to pipeline ingestion from PostGIS.
Remote PostGIS
Remote connections allow Aurora to use PostGIS tables directly without copying data.
Remote datasets remain in the source database and are accessed live.
Remote connections support two storage models:
View (live query)
Materialized View (local cached)
Remote data can be used in maps, dashboards, and analysis.
Import Mode
PostGIS Import retrieves spatial tables and stores them as Aurora datasets.
Import configuration includes:
Host
Port
Database
Schema
Table
Geometry column
ID column (optional)
Imports can be:
One-off ? single ingestion
Scheduled ? recurring updates
Scheduled imports keep Aurora datasets synchronized with PostGIS.
Remote Mode
Remote PostGIS uses database tables directly without ingestion.
Remote configuration includes:
Host
Port
Database
Schema
Table
Geometry column
ID column (optional)
Aurora creates a spatial data reference pointing to the external table.
Remote Storage Options
Remote connections provide two execution models.
View (Live)
Aurora queries the PostGIS table directly at runtime.
Characteristics:
No local storage
Always current
Depends on remote database performance
No Aurora indexing
Best for:
Frequently updated data
Operational databases
Live analysis
Large tables
Materialized View
Aurora creates a locally stored materialized view of the remote table.
Characteristics:
Local copy in Aurora database
Local spatial indexes
Faster rendering and analysis
Refresh scheduling available
Materialized views balance live data with performance.
Normalization
Remote tables can be normalized for Aurora use.
Normalization defines:
Geometry column
ID column
Spatial data identifier
This ensures compatibility with maps, dashboards, and analysis.
Scheduling
Both Import and Materialized View modes support scheduling.
Scheduling enables:
Automatic refresh
Database synchronization
Live dashboard updates
Pipeline-like behavior
Import refreshes Aurora datasets.
Materialized View refreshes cached remote data.
Relationship to Live Analysis
Remote PostGIS connections are commonly used with Live Analysis.
Live Analysis tools operate directly on PostGIS data without ingestion.
See Live Analysis.
Relationship to Pipelines
PostGIS Import uses the Aurora Pipeline framework.
Pipelines ingest PostGIS tables into Aurora datasets.
See Pipelines.
Typical Uses
PostGIS Import:
Stable datasets
Analytical layers
Map publishing
Dashboards
Data transformation
Remote View:
Operational GIS databases
Frequently updated tables
Monitoring dashboards
Live spatial data
Materialized View:
Large datasets
Performance-critical maps
Cached enterprise data
Hybrid live/local workflows