We have a multi-tenant service where each customer has millions of users (total: ~150M rows). Now we would like to let each customer define some custom columns for his users and then let the customer search his users efficiently based on these columns.
This problem seems really hard to solve with PostgreSQL:
In particular the easiest way would be to add a JSON field on the users table (e.g. user metadata). However the PostgreSQL GIN index only supports exact matches and not range queries. This means that a query on a range (e.g. age > 30) would be extremely inefficient and would result in a table scan.
You could have a table of (tenant, customer, setting_name, setting_value) so that a btree index on (tenant, setting_name, setting_value) would work for "select customer from my_table where tenant=$1 and setting_name='age' and setting_value > 30"
That doesn't deal with setting values having a variety of types, but you could have a distinct user defined settings table for each setting value type that you want to support.
