Efficient data processing is critical for interactive visualization of analytic data sets. Inspired by the large amount of recent research on column-oriented stores, we have developed a new specialized analytic data engine tightly-coupled with the Tableau data visualization system.The Tableau Data Engine ships as an integral part of Tableau 6.0 and is intended for the desktop and server environments. This paper covers the main requirements of our project, system architecture and query-processing pipeline. We use real-life visualization scenarios to illustrate basic concepts and provide experimental evaluation.

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Efficient and convenient handling of heterogeneous data is a current challenge for data management systems. In this paper, we discuss several common relational approaches to represent heterogeneity and argue for a design based on a single wide-table, referred to as a flexible schema. For this scenario, we focus on partial indexation and its support for efficient data storage and processing.Filtered indices provide partial indexation functionality in the Microsoft SQL Server product. We describe here the implementation of this feature, including index utilization in queries, index maintenance and query parameterization issues. Our performance experiments validate the expected benefits of the approach in our implementation.

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