A knowledge graph (KG) is a multidirectional labelled graph used for the graphical representation of knowledge where each node represents an entity, and the edge connecting the two nodes represents a relationship. There has been a rise in the popularity of using KG in information retrieval, recommender system, dialogue system, and question-answering system (QAS). The QAS can be either over structured data or unstructured data. This article studies the existing techniques for question-answering systems over KG (KGQA). We collect more than 30 articles on the question-answering system over a knowledge graph. We give a brief introduction to KG and QAS. Further, we discuss challenges, datasets and evaluation metrics used to evaluate techniques. Finally, we conclude the article by discussing some open research aspects, highlighting factors of the low-resource language for KGQA task and remarks on existing systems.