Trie trees can be helpful for searching strings, but they also have some big challenges that can make them tricky to use.

1. Space Problems: Tries can take up a lot of memory, especially when you have many strings that share the same beginning. The nodes in a trie can grow quickly, which isn’t a good use of space. In the worst cases, if you have $n$ strings, each $m$ characters long, the space used can be $O(n \cdot m)$.

2. Speed Issues: Tries are supposed to be fast, allowing you to search, add, or delete strings in $O(m)$ time (where $m$ is the string length). But this only works if the trie is well-organized. If it isn't, searching can take longer, especially for strings with few shared beginnings. In some cases, it could take up to $O(n)$ time to find what you need.

3. Hard to Set Up: Building a trie isn’t always easy. You need to manage the nodes carefully and handle memory well, which can make it difficult to create.

To help with these problems, you can use methods like compression (such as a ternary search tree or a mix of different methods) to save space and manage the nodes better. Also, using lazy deletion can make it easier to remove strings, which helps keep the trie balanced and working well overall.