Abstract

Big Data has driven the need for datastores that can scale horizontally leading to the development of many different NoSQL database implementations, each with different persistence and query philosophies. Spatio-temporal data such as location data is one of the largest types of data being collected today. We describe a novel spatio-temporal index structure that leverages the horizontal scalability of NoSQL databases to achieve performant query and transformation semantics. We present performance characteristics gathered from testing with Accumulo.

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