In recent years, engineering software platforms aimed at supporting the development and integration of applications and services for smart cities has become increasingly significant and some initiatives have gained traction to pursue environmental, economic and social goals. Decision science plays a crucial role and needs to be incorporated into such platforms to inform and make decision-making more effective. To address these challenges, self-adaptation (SA) and big data analytics (BDA) are two prominent approaches for decision science that have not yet been sufficiently explored in the context of smart city. This paper presents the results of a systematic literature review on software platforms for smart cities, with a focus on SA and BDA, and their interrelation. This review can benefit both researchers and practitioners in the field, who can use it as a reference for conceiving smart city platforms that enable seamless integration and cooperation of diverse and competing city services, leveraging SA and BDA for decision science.