Native Replication of Postgres Geospatial Data

PostGIS extension enables you to efficiently store and query geospatial data in Postgres. It introduces spatial data types such as GEOMETRY and GEOGRAPHY, which lets you store points, polygons, lines and so on. PostGIS also supports a large set of SQL functions and spatial indexes to effectively manipulate spatial data.
The reason you chose PostGIS is that you want your geospatial workload to be treated as a first-class citizen. You should expect no less when it comes to replicating your geospatial database, instead of geospatial being an afterthought.
In this blog, we will explore what it takes to natively replicate PostGIS data from Postgres to other data stores.
Status Quo
We've overwhelmingly heard from customers that existing data movement tools are not reliable in replicating geospatial data from Postgres. Common issues include -
Suboptimal Data Type Conversion - converting spatial types to STRING or JSON rather than using native spatial types supported by the target.
Data Loss - skipping whole rows when encountering incompatible types leading to loss of data.
Replicating Geospatial data from Postgres
At PeerDB, we are building a specialized data-movement tool for Postgres. With that spirit, we took a step forward to add extensive geospatial support while replicating data from Postgres to Snowflake. This includes -
Demo of replicating Postgres Geospatial data incl. POINT, LINE, POLYGON etc of GEOMETRY and GEOGRAPHY types to Snowflake.
Support for GEOMETRY and GEOGRAPHY data types: These types are stored as GEOMETRY and GEOGRAPHY types on Snowflake.
Replicating Points, Lines and Polygons: A GEOMETRY or GEOGRAPHY in Postgres can be any of a Point, Line or Polygon. PeerDB handles replicating all these data types to Snowflake.
Let's see how to ingestPoint,LineandPolygonto a Postgres table:CREATE TABLE locations ( id serial PRIMARY KEY, location_name VARCHAR(255), location_geometry GEOMETRY, location_geography GEOGRAPHY ); -- Inserting a point with generic geometry and geography INSERT INTO locations VALUES (1,'Point A', ST_GeomFromText('POINT(1 2)'), ST_GeogFromText('POINT(1 2)')); -- Inserting a line with generic geometry and geography INSERT INTO locations VALUES (2, 'Line AB', ST_GeomFromText('LINESTRING(1 2, 3 4, 5 6)'), ST_GeogFromText('LINESTRING(1 2, 3 4, 5 6)')); -- Inserting a polygon with generic geometry and geography INSERT INTO locations VALUES (3, 'Polygon ABCD', ST_GeomFromText('POLYGON((1 1, 2 1, 2 2, 1 2, 1 1))'), ST_GeogFromText('POLYGON((1 1, 2 1, 2 2, 1 2, 1 1))'));Replicating GEOMETRYCOLLECTION: A geometry can represent a collection of Lines, Points and Polygons. PeerDB handles replicating
GEOMETRYCOLLECTIONfrom Postgres to Snowflake.
Let's see how to insert aGEOMETRYCOLLECTIONto a Postgres table:/* Inserting a GEOMETRYCOLLECTION into the generic geometry column */ INSERT INTO locations (location_name, location_geometry, location_geography) VALUES ( 'GeometryCollection', ST_GeomFromText('GEOMETRYCOLLECTION(POINT(1 2), LINESTRING(1 2, 3 4))'), ST_GeogFromText('GEOMETRYCOLLECTION(POINT(1 2), LINESTRING(1 2, 3 4))') );Error handling for invalid Geometries: A difference between Postgres and Snowflake is that Postgres lets you store invalid Geometries and Snowflake doesn't. For example, a line with a single point can be stored in Postgres but not in Snowflake. In such a scenario, while replicating data from Postgres, PeerDB captures the invalid data in logs and stores
nullfor that column value on Snowflake.
Let's see how an invalidGEOMETRYlooks like in Postgressource=> SELECT ST_IsValid(ST_MakeLine('POINT(1 2)'::geometry)); NOTICE: Too few points in geometry component at or near point 1 2 st_isvalid ------------ f (1 row)
Conclusion
We added extensive support to replicate geospatial data from Postgres to Snowflake. We will be expanding this to other data stores such as BigQuery and Clickhouse. Please reach out to us if you want this support for other data stores.
If you want to give PeerDB a try for replicating geospatial data from Postgres, these links should prove useful: :)
Comments
Join the discussionReally interesting discussion on native replication for Postgres geospatial data. Geospatial workloads often introduce additional complexity because of large datasets, spatial indexes, replication lag, and PostGIS dependencies. I like how the article highlights the importance of logical replication and architecture planning when handling distributed geospatial environments.
Many organizations working with GIS and spatial analytics are now looking for scalable replication strategies that balance performance, consistency, and regional availability. Community discussions around PostGIS, FDW, and logical replication also show how important replication architecture has become for modern geospatial applications.
This is a very valuable topic for data engineering and geospatial teams working with enterprise-scale PostgreSQL deployments.
Sounds cool! Might even be useful for a current project - we are aggregating a lot of geospartial data using strings, it has a lot of downsides.
Thanks Lev for the comment. Glad to hear that this could be useful for a current project. Do you store the geospatial data in Postgres?
Yea, I currently store all of the data as a string and json format on Postgres.





