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Cloud computing, as a concept, promises cost savings to end-users by letting them outsource their non-critical business functions to a third-party in pay-as-you-go style. However, to enable economic pay-as-you-go services, the end-users need Cloud middleware that maximizes sharing and support near-zero cost for unused applications. Multi-tenancy, which let multiple tenants to share a single application instance securely, is a key enabler for building such a middleware. On the other hand, Business processes capture Business logic of organizations in an abstract and reusable manner, and hence play a key role in most organizations. This paper presents the design and architecture of a scalable Multi-tenant Workflow engine while discussing in detail the potential use cases of such architecture. Primary contributions of this paper are motivating workflow multi-tenancy, and the design and implementation of a scalable multi-tenant workflow engine that enables multiple tenants to run their workflows securely within the same workflow engine instance without modifications to the workflows. Furthermore, the workflow engine supports process sharing and process variability across the tenants and discusses its ramifications.

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To stay competitive in today's data driven economy, enterprises large and small are turning to stream processing platforms to process high volume, high velocity, and diverse streams of data (fast data) as they arrive. Low-level programming models provided by the popular systems of today suffer from lack of responsiveness to change: enhancements require code changes with attendant large turn-around times. Even though distributed SQL query engines have been available for Big Data, we still lack support for SQL-based stream querying capabilities in distributed stream processing systems. In this white paper, we identify a set of requirements and propose a standard SQL based streaming query model for management of what has been referred to as Fast Data.