InnoDB clearly requires far more memory for these reasons, but it gets slightly difficult to pin down exactly how much more memory. This is true for several reasons:
a. How did you load your database?
InnoDB table size is not a constant. If you took a straight SQL dump from a MyISAM table and inserted it into an InnoDB table, it is likely larger than it really needs to be. This is because the data was loaded out of primary key order and the index isn’t tightly packed because of that. If you took the dump with the order by primary argument to mysql dump, you likely have a much smaller table and will need less memory to buffer it.
b. What exactly is your table size?
This is an easy question to answer with MyISAM: that information is directly in the output of “SHOW TABLE STATUS”. However, the numbers from that same source for InnoDB are known to be estimates only. The sizes shown are the physical sizes reserved for the tables and have nothing to do with the actual data size at that point. Even the row count is a best guess.
c. How large is your primary key?
It was mentioned above that InnoDB clusters the data for a table around the primary key.This means that any secondary index leaves must contain the primary key of the data they “point to.” Thus, if you have tables with a large primary key, you will need more memory to buffer a secondary index and more disk space to hold them. This is one of the reasons some people argue for short “artificial” primary keys for InnoDB tables when there isn’t one “natural” primary key.
In summary, there is no set method that will work for everyone to predict the needed resources. Worse than that, your needed resources will change with time as more inserts to your table increase its size and fragment the packing of the BTree. The best advice to be offered is use the mysql report tool available here (http://hackmysql.com/mysqlreport) to monitor your available innodb_buffer_pool and adjust accordingly, the most important InnoDB tunable. It is important to not run at 100% usage of the innodb buffer, as this likely means that you’re not buffering as much as you could for reads, and that you are starving your write buffer which also lives in the same global innodb_buffer.