Stream reasoning is an approach that blends artificial intelligence and stream processing to make sense of multiple, heterogeneous data streams in real-time. It allows querying and reasoning over data streams using ontologies to represent streaming data. Deductive stream reasoning uses rules and ontologies while inductive stream reasoning uses machine learning to continuously learn from streaming data and adapt to concept drift. Stream reasoning has been studied in over 1000 scientific papers in the last 12 years and shows promise in addressing the challenges of volume, velocity, variety and veracity in big streaming data.