Does splitting tables in DB help with performance issue?

I just come up with a problem recently.

I am working in a project with开发者_Python百科 my friend, while my friend design the database, he splited same kind of data into different tables according to month(one table per month). His reason for this is for DB performance.

I'm a little doubt this solution, since he put all tables into one single machine, so I think the performance would be just the same as building an index for date.

Can anyone discuss this and give me some hints?

Unless there are more than approximately tens of millions of rows per month, then splitting is not a good idea and will NOT provide any more DB performance.

You will get much better performance gains by identifying the correct indexes for your query workload.

When you have have many millions of rows per month, then partitioning a table into date ranges might improve performance in certain situations (depends on query workload).

This may actually have sense if other options like the MERGE storage engine and built-in MySQL partitioning does not work for you, which seems to be not the case.