The twenty-first century has been dominated by the need for large scale data processing, marking the birth of big data platforms such as Cosmos. This paper describes the evolution of the exabyte-scale Cosmos big data platform at Microsoft; our journey right from scale and reliability all the way to efficiency and usability, and our next steps towards improving security, compliance, and support for heterogeneous analytics scenarios. We discuss how the evolution of Cosmos parallels the evolution of the big data field, and how the changes in the Cosmos workloads over time parallel the changing requirements of users across industry.

XML is commonly supported by SQL database systems. However, existing mappings of XML to tables can only deliver satisfactory query performance for limited use cases. In this paper, we propose a novel mapping of XML data into one wide table whose columns are sparsely populated. This mapping provides good performance for document types and queries that are observed in enterprise applications but are not supported efficiently by existing work. XML queries are evaluated by translating them into SQL queries over the wide sparsely-populated table. We show how to translate full XPath 1.0 into SQL. Based on the characteristics of the new mapping, we present rewriting optimizations that dramatically reduce the number of joins. Experiments demonstrate that query evaluation over the new mapping delivers considerable improvements over existing techniques for the target use cases.

XML is commonly supported by SQL database systems. However, existing mappings of XML to tables can only deliver satisfactory query performance for limited use cases. In this paper, we propose a novel mapping of XML data into one wide table whose columns are sparsely populated. This mapping provides good performance for document types and queries that are observed in enterprise applications but are not supported efficiently by existing work. XML queries are evaluated by translating them into SQL queries over the wide sparsely-populated table. We show how to translate full XPath 1.0 into SQL. Based on the characteristics of the new mapping, we present rewriting optimizations that minimize the number of joins. Experiments demonstrate that query evaluation over the new mapping delivers considerable improvements over existing techniques for the target use cases.

Microsoft SQL Server 2008 adds built-in support for 2-dimensional spatial data types for both planar and geodetic geometries to address the increasing demands for managing location-aware data. SQL Server 2008 also adds indexing capabilities that, together with the necessary plan selections done by the query optimizer, provide efficient processing of spatial queries. This paper will present an overview of the spatial indexing implementation in SQL Server 2008 and outline how the indexing is implemented and how the cost-based query optimizer chooses among the different plans.

Microsoft® SQL Server™ has a long history of XML support dating back to 1999. While first concentrating on enabling the transport of relational data via XML with the SQL Server 2000 release, SQL Server 2005 now additionally provides native XML storage and query support. This part of the tutorial will provide an insight into how SQL Server 2005 fits XML functionality into its core relational database management framework.

As XML has evolved from a document markup language to a widely-used format for exchange of structured and semistructured data, managing large amounts of XML data has become increasingly important. A number of companies, including both established database vendors and startups, have recently announced new XML database systems or new XML functionality integrated into existing database systems. This tutorial will provide an insight into how XML functionality fits into relational database management systems as seen by three major relational vendors: IBM, Microsoft and Oracle.

Loosely-coupled, distributed system architectures need to be flexible enough to allow individual components to join or leave the heterogeneous conglomerate of services and components and to change their internal design and data models without jeopardizing the whole architecture. A well-established approach is to use XML as the lingua franca for the integration layer that hides the heterogeneity among the components and provides the glue that allows the individual components to take part in the loosely integrated system. The article focuses on how to provide the basic technology to enable a relational database to become a component in such loosely-coupled systems and it provides an overview of the features that are needed to provide access via HTTP and XML.