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白皮书-DBMod Microsoft SQL Server 2019 Big-Data-Clusters

白皮书-DBMod Microsoft SQL Server 2019 Big-Data-Clusters

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For 25 years, Microsoft SQL Server has been powering data-driven organizations. Relational databases have long been the norm and still hold a prominent place in any organization’s data architecture. As the variety of types of data and the volume of that data has risen, the number of types of databases has risen dramatically. Today there are NoSQL databases, graph databases, in-memory databases, and big data provided by an ever-growing number of software vendors. Over the years, SQL Server has kept pace by adding support for XML, JSON, in-memory, and graph data in the database. It has become a do-it-all, flexible database engine that enterprises can count on for industry-leading performance, high availability, and security. However, with its roots in a relational engine, a single instance of SQL Server was never designed or built to be a database engine for analytics on the scale of petabytes or exabytes. It also was not designed for scale-out compute for data processing or machine learning, nor for storing and analyzing data in unstructured formats, such as media files. SQL Server 2019 extends its unified data platform to embrace big and unstructured data by integrating Spark and HDFS into a “big data cluster”.
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