Published In

7th Biennial Conference on Innovative Data Systems Research (CIDR ’15) January 4-7, 2015, Asilomar, California, USA.

Document Type

Presentation

Publication Date

2015

Subjects

Big Data Applications, Data Management

Abstract

Data management and analytics systems for big data have proliferated, including column stores, array databases, graphanalysis environments and linear-algebra packages. This burgeoning of systems has lead to a surfeit of language and APIs. It is time to consider a new framework that can span these systems and simplify the programming and maintenance of Big Data applications. There are two key goals for such a framework:

Portability: It should be relatively easy to move an application or tool developed on one platform to operate against another. As a corollary, back-end data and analytics services should be swappable in a particular platform.

Multi-Server Applications: It will be more common than not that a given application will need the services of multiple systems. The framework should make is easy to construct and deploy such applications.

Persistent Identifier

http://archives.pdx.edu/ds/psu/16664

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