Kahn's Algorithm and the DFS-based approach are two great methods for sorting items in directed acyclic graphs, or DAGs for short. They help us understand the order in which things need to happen, but they do it in different ways.

Kahn's Algorithm:

• Time Complexity: This means how long the algorithm takes to run. It’s $O(V + E)$, where $V$ is the number of points (vertices) and $E$ is the number of connections (edges). This method looks at each point and each connection just one time.

• Space Complexity: This is about how much memory (space) we need. Kahn's Algorithm uses $O(V)$ space to keep track of how many connections lead to each point and for the list that helps manage points with no incoming connections.

DFS-Based Approach:

• Time Complexity: Just like Kahn's, the time it takes is also $O(V + E)$. This is because we look at every connection and point during the depth-first search, a method of exploring graphs.

• Space Complexity: The space used is $O(V)$ as well. This includes the memory for the recursive calls (if done that way) and for the list where we store our results.

In summary, both methods are pretty efficient. Which one you choose might depend on what you need to do or what you like better. Personally, I often prefer Kahn's Algorithm. It’s easier to work with, especially when dealing with big graphs!