We develop compression methods for functional tries and study them experimentally. Trie compression is usually implemented either as a combination of path compression and width compression or as a combination of path compression and level compression. We develop a new efficient implementation for width compression and show that in functional tries the combination of all of the three compression methods yields the best results when taking into account the trie size, the trie depth, the copy cost, and the search and update performance. We also show that the 2-3 tree minimizes the copy cost in balanced trees and compare our experimental results for tries to approximate analytical results for internal and external 2-3 trees. Our conclusion is that the path-, width- and level-compressed trie is an ideal choice for a functional main-memory index structure.