Information retrieval applications increasingly have to deal with multimedia content. Since image and video databases became ever larger, scalability is a critical requirement for visual information retrieval. This chapter first describes the types of processes that support either content-based retrieval or mining and have to scale. The nature of the problems to be solved and the principle of the solutions are presented next. An emphasis is put on key ideas supporting recent progress, like the use of approximation or of shared-neighbor similarity. To keep the pace with the evolution of scalability requirements, due to more complex visual descriptions and higher volumes of data, further advances are needed. Embeddings, filtering based on simplified descriptions, optimization of content representations and distributed processing are a few directions that deserve being followed.