I have a system with 5 source data stores (mostly PostgreSQL databases) from which, I want to connect them all to containers running on OpenShift: A library of react applications who's components make AJAX requests for data feeds from a thin server instance that is also running on OpenShift.

So far I have created the following:

  • A test server (Flask with flask_restful and sqlalchemy) that has a direct connection to one of the data stores and can returns REST JSON responses of any of the tables in the database being requested
  • A node.js app consisting of two react components (D3.js visual and data table) which on mount/update, consume JSON response of one of the database's tables

In the production system, my plan is to add in:

  • graphQL to avoid the over-fetching that I'm currently doing
  • Connect up my server with a redis data cache to reduce demand on the data stores

My Question:

As some of the data coming from the data stores can be large (>1M records), what would be the optimal way to do this?

  • Should I rewrite my server with node.js (my thinking being that javascript is 'native' to JSON and so faster processing?)
  • I have been looking into BSON and msgpck but I'm unclear if these would play nicely with react components?
  • Is there a scenario where I could optionally pass data between the OpenShift applications rather than sending large JSON response objects?
  • Could you indicate whether you solved the issue?
    – 030
    Dec 23 '19 at 10:13
  • @030 unfortunately not!
    – Bendy
    Dec 23 '19 at 14:52
  • Could you indicate when a response is fast and when slow? E.g. X<100ms?
    – 030
    Dec 23 '19 at 15:01

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