Abstract
The production environment for analytical data management applications is rapidly changing. Many enterprises are shifting away from deploying their analytical databases on high-end proprietary machines, and moving towards cheaper, lower-end, commodity hardware, typically arranged in a shared-nothing MPP architecture, often in a virtualized environment inside public or private "clouds". At the same time, the amount of data that needs to be analyzed is exploding, requiring hundreds to thousands of machines to work in parallel to perform the analysis. There tend to be two schools of thought regarding what technology to use for data analysis in such an environment. Proponents of parallel databases argue that the…
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5Topics & keywords
Topics
Keywords
- Computer science
- Scalability
- Flexibility (engineering)
- Fault tolerance
- Distributed computing
- Architecture
- Big data
- Database
UN Sustainable Development Goals
- Industry, innovation and infrastructure
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