Recommender systems mainly utilize for finding and recover contents from large datasets; it has been determining and analysis based on the scenario—Big Data. In this paper, we describe the process of recommendation system using big data with a clear explanation in representing the operation of mapreduce. We demonstrate the various stage of recommendation namely data collection rating, types of filtering. Analysis Scenario based drug recommender system, it consists of three components namely drug storage, cloud server, and recommender server. The system is evaluating with specific parameters like F-score, Precision, and recall. Finally, we describe the challenge of recommendation systems like data sparsity, cold start, sentimental analysis and No surprise. © Springer Nature Singapore Pte Ltd. 2019.