Raster data consists of a matrix of cells or pixels. The cells or pixels are organized into rows and columns to form a grid. Each cell contains a value that represents information, such as temperature.


Raster data can be digital aerial photographs, satellite images, digital images, or scanned maps.

PolarDB for PostgreSQL and PolarDB-O implement the raster model. This allows Ganos to store and analyze raster data in a cost-effective manner with the help of database technologies and methods.

Quick start

  • Create an extension.

    Create Extension Ganos_Raster cascade;
  • Create a raster table.

    Create Table raster_table(id integer, raster_obj raster);
  • Import raster data from Object Storage Service (OSS).

    Insert into raster_table Values(1, ST_ImportFrom('chunk_table','OSS://ABCDEFG:1234567890@oss-cn.aliyuncs.com/mybucket/data/4.tif'))
  • Query raster object information.

    Select ST_Height(raster_obj),ST_Width(raster_obj) From raster_table Where id = 1;
  • Create a pyramid.

    Update raster_table Set raster_obj = ST_BuildPyramid(raster_obj) Where id = 1;
  • Calculate the optimal pyramid level based on the world space, width, and height of a viewport.

    Select ST_BestPyramidLevel(raster_obj, '((128.0, 30.0),(128.5, 30.5))', 800, 600) from raster_table where id = 10;
  • Retrieve a pixel matrix from the specified space of a raster object.

    Select ST_Clip(raster_obj, 0, '((128.980,30.0),(129.0,30.2))', 'World') From raster_table Where id = 1;
  • Calculate the raster space of a clipped area.

    Select ST_ClipDimension(raster_obj, 2, '((128.0, 30.0),(128.5, 30.5))') from rater_table where id = 10;
    '((600, 720),(200, 300))'
  • Delete the extension.

    Drop Extension Ganos_raster cascade;

SQL reference

For more information, see Raster SQL reference.