I've found that partitioning doesn't do much in the area of performance except to usually make it slower even if your code is written well enough to take advantage of so called partition elimination. A monolithic table with the correct indexes and the correct code playing against it will usually beat the identical index/code combination on a partitioned table. I say "usually" a bit tongue in cheek because I've not yet seen a partitioned table beat a monolithic table for performance.
My disclaimer there is that I have seen some people claim that partitioning helped performance but, for those I'm aware of, it was the indexing they had to do to partition the tables that really made the difference. Doing similar indexing on their old monolithic table was still faster. Fixing bad code is even better.
Partitioning <> Performance. What partitioning is really good for is index maintenance, backups, and the ability to do "Piece Meal" restores if the need should ever arise.
is pronounced "ree-bar
" and is a "Modenism
" for R
First step towards the paradigm shift of writing Set Based code:
________Stop thinking about what you want to do to a row... think, instead, of what you want to do to a column.
"If you think its expensive to hire a professional to do the job, wait until you hire an amateur."--Red Adair
"Change is inevitable... change for the better is not."
When you put the right degree of spin on it, the number 3|8
is also a glyph that describes the nature of a DBAs job. 😉
How to post code problems
Create a Tally Function (fnTally)