12 ms·

And what are the results of your decision in terms of performance?

• cyberax 2y ago
  These days? It doesn't really matter. For most purposes, you can just hold the entire important dataset in RAM. For example, a humongous company with 500000 employees (Amazon) can trivially hold on a fairly low-end server the database of all the personnel, and all their salary payments, and all their employment history, badge photos, and office access logs.
• halflife 2y ago
  The DB is rarely our bottleneck. Our reads are very simple, mostly paged sets from a table with a 1 level join. When we need complex abstractions or transformations, instead of using function or views, we listen to table changes, and with a TS transformation layer we save a new row in a specific table for the abstraction. That way the BL is handled in TS, and performed in writes asynchronously instead of in-line in reads. The only downside is that the transformed data is not real time. That mechanism allowed us to scale our data very easily without any performance hits.