In this big data era, it is hard for the current generation to find the right data from the huge amount of data contained within online platforms. In such a situation, there is a need for an information filtering system that might help them find the information they are looking for. In recent years, a research field has emerged known as recommender systems. Recommenders have become important as they have many real-life applications. This paper reviews the different techniques and developments of recommender systems in e-commerce, e-tourism, e-resources, e-government, e-learning, and e-library. By analyzing recent work on this topic, we will be able to provide a detailed overview of current developments and identify existing difficulties in recommendation systems. The final results give practitioners and researchers the necessary guidance and insights into the recommendation system and its application.