Posted On: Aug 19, 2021
With the today's performance enhancements you can significantly enhance geometry query throughput by up to 100x in some cases transparently and automatically. The performance enhancements also optimize and accelerate spatial queries with large table JOINs. Support for 3D/4D geometries in spatial queries greatly expands the range of spatial use cases where 3D/4D spatial coordinates is required to accurately represent the multi-dimensional data.
In addition to the above new spatial features, there are more than 8 new spatial functions that we’re announcing today that are part of the expanding spatial engine in Redshift. Some of the noteworthy spatial functions that you can use to build complex spatial applications include: ST_ConvexHull computes the convex hull of a geometry; ST_LineInterpolatePoint returns a point interpolated along a line; ST_Reverse can be used on any geometry and reverses the order of the vertices; ST_LengthSphere returns the length of a linear geometry in meters. Some additional functions used in conjunction with the above functions include: ST_MakeLine takes an aggregate geometry type and creates a LineString containing points that could include Point, MultiPoint, or LineString geometries.
About Amazon Redshift spatial: Amazon Redshift launched native spatial data processing support in November 2019, with a polymorphic data type GEOMETRY, and several key SQL spatial functions. With today's announcement, our library of spatial functions has grown to 80. This capability enables you to store, retrieve, and process spatial data so you can enhance your business insights by integrating spatial data into your analytical queries. Amazon Redshift spatial data processing functionality is available to new and existing customers at no additional cost. To get started and learn more about Redshift spatial feature, visit our documentation.
Redshift spatial feature is available in all public AWS regions. Refer to the AWS Region Table for Amazon Redshift availability.