Article Robert Cemper · Aug 8, 2017 1m read

In a previous exercise, I was able to show the power of Caché.
A medium-designed set of interdependent tables with some GB of data.
URLs cross reference over some million pages resulting in ~3 billion records

Competition was between

  • Caché
  • PostgreSQL
  • MySQL

Criteria were Speed + Storage consumption
I composed  a customized loader fed over a "raw" TCP connection
Mapping the "objects" into the final table by directly writing to Global Storage.

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Article Robert Cemper · Aug 5, 2017 3m read

GIS stands for Geographic Information System.
  and it's not a typical arena for Caché. But it's definitely an environment with high data volume.
You see 3 major areas

- Visual front end:
   A mature area well covered by a bunch of commercial and open source products.
   No need for Caché there.

- GIS mathematics:  
  JTS (Java Topology Suite)  is fixed standard that covers all requirements and can be linked to Caché by the Java Gateway
or the C, C++ incarnation of this standard library using Caché Call Out Gateway.
  So far no added value by Caché.

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