In recent years, Big Data has become high-focus of researchers as many organizations have been processing huge amount of information. We face a diversity of datasets from different sources in different domains such as Flickr, Twitter, YouTube, Facebook and other local data centers. In this big data era, Video data face its new challenges to store and retrieve, since the size of video data is high and the processing and analysis methods are very complex. Over past years, various ideas and techniques have been proposed towards the effective storage and retrieval of video contents. This paper summarizes the description of the background to common approaches in visual content-based big video storage and retrieval. It also provides a systematic classification of most recent technical works on feature representation, video analysis methods such as video segmentation/video content structuring, video summarization, video abstraction, video indexing, and finally, future challenges and opportunities of big video data. The underlying components for each approach are identified and the details on how they are addressed in specific works were discussed. © Research India Publications.