With social networks, the Web, connected objects, and an increasingly connected population, there is a strong increase in data coming from multiple and diverse sources and having different structures. This has, among other things, contributed to the advent of the notion of Big Data. These data allow companies to add value to the changing needs of their markets. However, managing the volume and nature of these data is proving complex. While some big companies have succeeded in managing Big Data and derive added value from it, particularly in the realization of profit and innovation, this is not the case for Small and Medium-sized Enterprises (SMEs) that do not have enough resources to manage Big Data. This makes the adoption of Big Data analytics in SMEs for sustainable development an interesting challenge and field of research. The aim of this paper is not only to review the literature to understand the work relating to Big Data and SMEs, but also to draw up a general taxonomy of Big Data and to propose a taxonomy of possible Big Data analytics use according to the different sectors and branches of activities for sustainable development. These taxonomies will make it possible to present a categorization of SMEs according to Big Data use. Moreover, this work shows advances in integrating Big Data analytics in SMEs, highlights their advantages and limits, and discusses the challenging open research issues that need to be focused on to provide guidelines for new contributions.