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Platform-as-a-service (PaaS) systems, such as Google App Engine (GAE), simplify web application development and cloud deployment by providing developers with complete software stacks: runtime systems and scalable services accessible from well-defined APIs. Extant PaaS offerings are designed and specialized to support large numbers of concurrently executing web applications (multi-tier programs that encapsulate and integrate business logic, user interface, and data persistence). To enable this, PaaS systems impose a programming model that places limits on available library support, execution duration, data access, and data persistence. Although successful and scalable for web services, such support is not as amenable to On-Line Analytical Processing (OLAP), which have variable resource requirements and require greater flexibility for ad-hoc query and data analysis.
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