Tearing Down the Tower of Babel: Unified and Efficient Spatio-temporal Queries for NoSQL Stores (Video Presentation)

NoSQL stores are used extensively for scalable storage and efficient querying of large spatio-temporal data collections in modern applications. Yet, despite their popularity, NoSQL systems have two main limitations when confronted with spatio-temporal data: (a) they do not offer optimized indexing methods, and (b) they still rely on heterogeneous languages and lack of standardization in data access, a situation bearing resemblance to the narrative of the tower of Babel. To address these limitations, in this paper propose NODA, a system for scalable querying of spatio-temporal data stored in different NoSQL stores in a unified way.