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I find it very common to want to model relational data in my functional programs. For example, when developing a web-site I may want to have the following data structure to store info about my users: data User = User { name :: String , birthDate :: Date } Next, I want to store data about the messages users post on my site: data Message = Message { user :: User , timestamp :: Date , content :: String } There are multiple problems associated with this data structure: We don't have any way of distinguishing users with similar names and birth dates. The user data will be duplicated on serialisation/deserialisation Comparing the users requires comparing their data which may be a costly operation. Updates to the fields of User are fragile -- you can forget to update all the occurences of User in your data structure. These problems are manageble while our data can be represented as a tree. For example, you can refactor like this: data User = User { name :: String , birthDate :: Date , messages :: [(String, Date)] -- you get the idea } However, it is possible to have your data shaped as a DAG (imagine any many-to-many relation), or even as a general graph (OK, maybe not). In this case, I tend to simulate the relational database by storing my data in Map s: newtype Id a = Id Integer type Table a = Map (Id a) a This kind of works, but is unsafe and ugly for multiple reasons: You are just an Id constructor call away from nonsensical lookups. On lookup you get Maybe a , but often the database structurally ensures that there is a value. It is clumsy. It is hard to ensure referential integrity of your data. Managing indices (which are very much necessary

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