Developers can use it easily in new applications and combine it with other SQL predicates. Nobody other solution besides SAP HANA offers this capability, and it is laborious to implement it in other relational databases using the basic geospatial functions.
Why supporting Hexagonal clustering is important for SAP HANA customers? It allows to represent curvatures and is ideal for showing path connectivity or movement. It is extremely useful for all spatial data processing in all industries.
Real-World Examples:
- Rescue management: finding evacuation paths and identifying evacuation zones. For example in case of a wildfire, you need to guide people from A to B, avoiding fire zones
- Trafficability: moving a battalion of tanks from A to B, without crossing risky muddy areas and woods.
- Utility grid planning: finding the right path for a new gas pipe, but you can't go underneath building, need to avoid protected lands and going over costly roads or rails.
Hexagonal clustering is a better way of getting insights from relational spatial data. It assign geometries within free definable area to the identified hexagonal pattern. Using hexagon grids reduce sampling bias due to edge effects of the grid shape.
How SAP HANA uniquely supports Hexagonal clustering?
SAP HANA is the only database that offers Hexagonal clustering out of the box.
SAP HANA clusters geocoordinates in a free definable area in an over-spanning grid of clusters in one SQL query. This can be combined with many other SQL features without coding (e.g. count(*), ST_UnionAggr, ST_Centroid, ST_Enveloper, …)) and runs on millions of coordinates in seconds.
Hexagonal clustering leverages SAP HANA spatial and graph capabilities.
Other exciting innovations to SAP HANA core spatial capability include:
- Memory footprint reduction by a factor 2 - To innovate faster and at a lower cost
- Open source support - SAP expanded support for geotools and geoserver: customers can now use free GIS systems instead of commercial GIS systems, expanding to new markets & targeting open source community. This is important and many GIS users prefer open source rather than commercial systems
