A nearest neighbourhood query (NHQ) retrieves the closest group of collocated objects from a spatial database for a given query location. On the other hand, a reverse nearest neighborhood query (RNHQ) returns all groups of collocated objects that find the given query nearer than any other competitors. Both NHQ and RNHQ queries might have many practical applications on mobile social networks, demand facility placement and smart urban planning. This paper also introduces another query, called direction-based spatial skyline query (DSQ), for retrieving surrounding objects from a spatial database for a given user location. The retrieved objects are not dominated by other data objects in the same direction w.r.t. the query. Like NHQ and RNHQ queries, retrieval of surrounding objects also has many applications such as nearby point-of-interests retrieval surrounding a user and digital gaming. This paper presents the challenges, algorithms, data indexing and data pruning techniques for processing NHQ, RNHQ and DSQ queries in spatial databases. Finally, encouraging experimental results and future research directions in NHQ, RNHQ, DSQ queries and their variants are discussed.