It is well established that we produce humongous amounts of information - technical infrastructures (smart grid, smart cities), the Social Web (Twitter, social networks, blogs), information systems (e-commerce, e-health), the media (newspapers, broadcasters), the Internet of Things, mobile phones, and many more - and that these amounts are growing exponentially. Linked Data gives us the technical means to network all this information and enables us to develop new forms of analytics on networked data from many sources instead of traditional "monolithic" data analytics. But this network of information is "in-discrete" as the data is produced continuously and at potentially high speeds with varying loads and demands on the producer and the consumer sides. This calls for new data/knowledge management approaches and as a result, the Linked Data world is slowly moving from a simplifying discrete model to a more realistic continuous view. This development impacts on and changes research problems in all areas and for all layers and requires well-orchestrated research efforts in and across research communities to support "streaming" as an integrated paradigm. In this talk, I will present a comprehensive stack of Linked Stream management approaches for all layers - from the Internet of Things to backend information systems, and will discuss the impact of streams on big data, analytics, and privacy.