This paper presents a new view of federated databases to address the growing need for managing information that spans multiple data models. This trend is fueled by the proliferation of storage engines and query languages based on the observation that "no one size fits all". To address this shift, we propose a polystore architecture; it is designed to unify querying over multiple data models. We consider the challenges and opportunities associated with polystores. Open questions in this space revolve around query optimization and the assignment of objects to storage engines. We introduce our approach to these topics and discuss our prototype in the context of the Intel Science and Technology Center for Big Data.
This paper presents BigDAWG, a reference implementation of a new architecture for "Big Data" applications. Such applications not only call for large-scale analytics, but also for real-time streaming support, smaller analytics at interactive speeds, data visualization, and cross-storage-system queries. Guided by the principle that "one size does not fit all", we build on top of a variety of storage engines, each designed for a specialized use case. To illustrate the promise of this approach, we demonstrate its effectiveness on a hospital application using data from an intensive care unit (ICU). This complex application serves the needs of doctors and researchers and provides real-time support for streams of patient data. It showcases novel approaches for querying across multiple storage engines, data visualization, and scalable real-time analytics.
In CIDR 2009, we presented a collection of requirements for SciDB, a DBMS that would meet the needs of scientific users. These included a nested-array data model, science-specific operations such as regrid, and support for uncertainty, lineage, and named versions. In this paper, we present an overview of SciDB's key features and outline a demonstration of the first version of SciDB on data and operations from one of our lighthouse users, the Large Synoptic Survey Telescope (LSST).
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