One of the most popular approaches to recommendation problems is Collaborative Filtering (CF).
This approach is based on the assumption that users who have agreed in the past, also tend to agree in the future. For example, if Alice likes Star Wars, Lord of the Rings and Harry Potter and Bob likes Stars Wars and Lord of the Rings too. Then it is likely that Bob would also enjoy Harry Potter. The collaborative in Collaborative Filtering is in relation to looking at the way that you multiple users interact with the same data and share the same commonalities.
Read on for a comparison of these four systems as well as a handy chart to help you figure out which system might work best for you.