The query planner has to do a linear search of the constraint information for every partition of tables used in the query, to figure out which are actually involved–the ones that can have rows needed for the data requested. The number of query plans the planner considers grows exponentially as you join more tables. So the exact spot where that linear search adds up to enough time to be troubling really depends on query complexity. The more joins, the worse you will get hit by this. The “up to a hundred” figure came from noting that query planning time was adding up to a non-trivial amount of time even on simpler queries around that point. On web applications in particular, where latency of response time is important, that’s a problem; thus the warning.
Can you support 500? Sure. But you are going to be searching every one of 500 check constraints for every query plan involving that table considered by the optimizer. If query planning time isn’t a concern for you, then maybe you don’t care. But most sites end up disliking the proportion of time spent on query planning with that many partitions, which is one reason why monthly partitioning is the standard for most data sets. You can easily store 10 years of data, partitioned monthly, before you start crossing over into where planning overhead starts to be noticeable.