A polystore system evaluates queries that span multiple disparate data models; this
character introduces a unique query optimization challenge. Specialized database engines …

Trajectory data are prevalent in systems that monitor the locations of moving objects. In a
location-based service, for instance, the positions of vehicles are continuously monitored …

Scientific applications are generating an ever-increasing volume of multi-dimensional data
that are largely processed inside distributed array databases and frameworks. Similarity join …

Filters trade off accuracy for space and occasionally return false positive matches with a
bounded error. Numerous systems use filters in fast memory to avoid performing expensive …

We have developed a reference implementation of the BigDAWG system: a new architecture
for future Big Data applications, guided by the philosophy that “one size does not fit all” …

Science applications are producing an ever-increasing volume of multi-dimensional data
that are mainly processed with distributed array databases. These raw arrays …

Persistent partitioning is effective in avoiding expensive shuffling operations. However it
remains a significant challenge to automate this process for Big Data analytics workloads …

Multidimensional arrays are a fundamental abstraction to represent data across scientific
domains ranging from astronomy to genetics, medicine, business intelligence, and …

Scientists are increasingly turning to datacenter-scale computers to analyze massive arrays.
Despite decades of database research that extols the virtues of declarative query …

Large-scale graph processing and Stream processing are two distinct computational
paradigms for big data processing. Graph processing deals with computation on graphs of …