Multidimensional Array Data Management

Multidimensional arrays are a fundamental abstraction to represent data across scientific domains ranging from astronomy to genetics, medicine, business intelligence, and engineering. Arrays come under multiple shapes — from dense rasters to sparse data cubes and tensors — and have been studied extensively across many computing domains. In this survey, we provide a comprehensive guide for past, present, and future research in array data management from a database perspective. Unlike previous surveys that are limited to raster processing in the context of scientific data, we consider all types of arrays — rasters, data cubes, and tensors. We identify and analyze the most important research ideas on arrays proposed over time. We cover all data management aspects, from array algebras and query languages to storage strategies, execution techniques, and operator implementations. Moreover, we discuss which research ideas are adopted in real systems and how are they integrated in complete data processing pipelines. Finally, we compare arrays with the relational data model. The result is a thorough survey on array data management that should be consulted by anyone interested in this research topic — independent of experience level.