Referring to the Postgres Documentation on Character Types, I am unclear on the point of specifying a length for character varying (varchar) types.
Assumption:
It does mention:
The storage requirement for a short string (up to 126 bytes) is 1 byte plus the actual string, which includes the space padding in the case of character. Longer strings have 4 bytes of overhead instead of 1. Long strings are compressed by the system automatically, so the physical requirement on disk might be less. Very long values are also stored in background tables so that they do not interfere with rapid access to shorter column values. In any case, the longest possible character string that can be stored is about 1 GB. (The maximum value that will be allowed for n in the data type declaration is less than that. It wouldn't be useful to change this because with multibyte character encodings the number of characters and bytes can be quite different.
This talks about the size of string, not the size of field, (i.e. sounds like it will always compress a large string in a large varchar field, but not a small string in a large varchar field?)
I ask this question as it would be much easier (and lazy) to specify a much larger size so you never have to worry about having a string too large. For example, if I specify varchar(50) for a place name I will get locations that have more characters (e.g. Llanfairpwllgwyngyllgogerychwyrndrobwllllantysiliogogogoch), but if I specify varchar(100) or varchar(500), I'm less likley to get that problem.
So would you get a performance hit between varchar(500) and (arbitrarily) varchar(5000000) or text() if your largest string was say 400 characters long?
Also out of interest if anyone has the answer to this AND knows the answer to this for other databases, please add that too.
I have googled, but not found a sufficiently technical explanation.
My understanding is that having constraints is useful for data integrity, therefore I use column sizes to both validate the data items at the lower layer, and to better describe the data model.
Some links on the matter: