Recommender system (RS) is a revolutionary technique which has transformed the applications from content based to customer centric. It is the method of finding what the customer wants, it can either be data or an item. The ability to collect and compute information has enabled the emergence of recommendation techniques, and these techniques provides a better understanding of users and clients. The innovation behind recommender frameworks has advanced in the course of recent years into a rich accumulation of tools that induces the researcher and scientist to create precise recommenders. This article provides an outline of recommender systems and explains in detail about the collaborative filtering. It also defines various limitations of traditional recommendation methods and discusses the hybrid extensions by merging spatial properties of the user (item-based collaborative filtering) with users personalized preferences (user-based collaborative filtering). This hybrid system is applicable to a broader range of applications. It helps the user to find the items of their interest quickly and more precisely. © Springer International Publishing Switzerland 2016.