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Scaling PostGIS Queries with Stado
Jim Mlodgenski, Cirrus Technologies
Stado, formerly know as GridSQL, provides a powerful and flexible analytical environment allowing users to process large amounts of data using a shared-nothing, massively parallel processing (MPP) architecture with PostgreSQL and PostGIS. Data is automatically partitioned across multiple nodes and each node processes its subset of data allowing queries to be distributed across the cluster and run in parallel. This fully open source architecture allows database performance to scale linearly as servers are added to the cluster while appearing as a single database to applications.
This presentation will demonstrate the 10-20x scalability and performance gains of spatial query running in a Stado environment compared to a single PostGIS instance. We will dig into how Stado plans a query capable of spanning multiple PostgreSQL servers and executes across those nodes using the Tiger data set as an example.
Jim Mlodgenski is a database architect with more than a decade of experience in enterprise database design and application development. As a member of the founding team and the former chief architect of EnterpriseDB, he is a pioneer in database migration technologies. Currently, he is the founder and CEO of Cirrus Technologies and a recognized leader in the PostgreSQL community.