It depends on whether the data point contains numeric, categorical or mixed data, and also on the purpose of the distance function. For numeric, Euclidian is simple, but cosine is robust to scaling and dtw is good for time series. For categorical, a basic one will be Jaccard similarity, which local sensitive hashing might apply.