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Greenplum Database is a massively parallel processing (MPP) database server with an architecture specially designed to manage large-scale analytic data warehouses and business intelligence workloads. MPP (a shared-nothing architecture) refers to systems with two or more processors that cooperate to carry out an operation, each with its own memory, operating system, and disks. Greenplum uses this high-performance system architecture to distribute the load of multi-terabyte data warehouses and can use all of a system’s resources in parallel to process a query. Greenplum Database is based on PostgreSQL open-source technology. It is essentially several PostgreSQL disk-oriented database instances acting together as one cohesive database management system (DBMS). It is based on PostgreSQL 12, and in most cases is very similar to PostgreSQL with regard to SQL support, features, configuration options, and end-user functionality. Database users interact with Greenplum Database as with a regular PostgreSQL DBMS.

PostGIS is an open-source spatial database extension for PostgreSQL, a powerful relational database management system. PostGIS adds support for geographic objects to the PostgreSQL database, turning it into a spatial database for geographic information systems (GIS). Whether you are new to PostGIS or looking to leverage its capabilities within the Greenplum ecosystem, this presentation aims to provide a comprehensive overview and practical insights into the seamless collaboration between PostGIS and Greenplum Database.

H3 is a geospatial indexing system developed by Uber Technologies. It provides a spatial indexing mechanism for mapping hexagons onto a sphere, making it particularly useful for applications involving geographic information, such as mapping, geospatial analytics, and location-based services. H3, a versatile hexagonal grid system, provides a unique spatial indexing mechanism that excels at handling geospatial data partitioning and aggregation.