Introduction
Overview of Spatial Support on the Cloud databases
Relational Databases
Managed Databases
Industry-standard databases are offered as a managed service on AWS, Azure, and Google Cloud.
| Database | Cloud Platform Support | Spatial Support | FME Support |
|---|---|---|---|
|
Maria DB (10.1.2+) |
|
Spatial Types: Geometry and Geography Supported Types: All main types. Spatial Functions: All major functions. |
Read, write and query. |
| MySQL ( 8.0+) |
|
Spatial Types: Geometry and Geography Supported Types: All main types. Spatial Functions: All major functions. |
Read, write and query. |
| Oracle |
|
Oracle Spatial and Oracle Locator are supported. Spatial Types: Geometry and Geography |
Read, write and query. |
| PostgreSQL |
|
All clouds support the PostGIS extension. Spatial Types: Geometry and Geography |
Read, write and query. |
| SQL Server |
|
Spatial Types: Geometry and Geography Supported Types: All main types. Spatial Functions: All major functions. |
Read, write and query. |
Cloud-Native Databases
Cloud-native databases are created by cloud providers and designed from the ground up to leverage the cloud architecture. They are often based on existing database engines but are optimized for the cloud with a focus on performance and availability.
| Database | Spatial Support | FME Support |
|---|---|---|
| AWS Aurora RDS |
Aurora supports both the MySQL and PostgreSQL database engines. Both of these engines have spatial data types enabled (PostGIS and MySQL). Spatial Types: Geometry and Geography |
Read, write and query. |
| Azure SQL Database |
This is based on SQL Server with the same spatial support. Spatial Types: Geometry and Geography |
Read, write and query. |
| Google Cloud Spanner |
Cloud Spanner does not natively support geospatial queries. Google’s S2 library can be leveraged which uses spherical geometry and is used by Google itself on Google Maps. This was deprecated in FME 2022 |
Read, write and query. |
Data Warehouses
Data warehouses are interactive tools for analyzing large datasets. They enable you to store large volumes of data cheaply and provide an interface where you can run fast, complex queries across the data.
| Database | Spatial Support | FME Support |
|---|---|---|
| AWS Athena |
Type of Support: Native Spatial Types: Geometry Supported Types: Points, Lines, Polygons, Multipoint, Multilines, Multipolygons and Geometry Collections Spatial Functions: Over 30 functions |
Query S3 datasets |
| AWS Redshift |
Type of Support: Native Spatial Types: Geometry and 2D support only. Supported Types: Points, Lines, Polygons, Multilines and Multipolygons Spatial Functions: Over 40 functions |
Read, write and query. |
| Google Big Query |
Type of Support: Native Spatial Types: Geography Supported Types: Points, Lines, Polygons. Spatial Functions: Over 30 functions. |
Read, write and query. |
| Snowflake |
Type of Support: Native Spatial Types: Geography Supported Types: Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection, Feature, FeatureCollection Spatial Functions: Over 30 functions. |
Read, write and query. |
NoSQL Databases
NoSQL databases enable the storage and querying of vast amounts of unstructured data.
| Database | Spatial Support | FME Support |
|---|---|---|
| AWS Dynamo DB | No support. There used to be support for geohashes via an official library, this project has now been archived. | Read and write. |
| Azure Cosmos DB |
Type of Support: Native Spatial Types: Geography and Geometry Supported Types: Points, Linestrings, Polygons, Multipolygons. Spatial Functions: Within, Distance, Intersects. |
Read, write and query. |
| Google Cloud Firestore |
Type of Support: No native support, but there is support for geohashing via a 3rd party library. Spatial Types: Geography Supported Types: Points Spatial Functions: Within, Distance, Bearing |
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