The `data.table` package might be useful to you. 

`data.table` works mostly by reference. Especially when assigning and modifying columns. 
Especially if you are hitting RAM limits, the efficiencies in data.table are dramatic

Additionally, data.table has built into the functionality of `with` `within` `by` `subset` etc, making calls much shorter and code more readable. 

For example, the cummbersome statement above could be simplified to something like:

    aDTofItems[attribute1 & attribute2==6 & attribute3=="C", # filter
               attribute4 := attribute5 * attribute6]        # assign

Furthermore, if the attributes you are filtering on are the `key` of the table, then the line is even shorter: 

    aDTofItems[.(TRUE, 6, "C"),     # filter
               attribute4 := attribute5 * attribute6]   # assign


Assuming the structure of each element is comparable, you can coerce your list into a data.table using 

    aDTofItems <- rbindlist(aListOfItems)
    # note, if you have factors in your list you should convert them to character before calling rbindlist

    # or similarly, although a bit slower 
    aDTofItems <- data.table(do.call(rbind, aListOfItems))