Good article on the topic: https://cmry.github.io/notes/euclidean-v-cosine
Cosine similarity is the angle between two points, while euclidean distance is the actual distance between two points. Cosine doesn’t care as much about magnitude so does well for different lengths of data (think how far into a specific direction something is as long as they are in that direction).