See Row mode memory grant feedback.Įnables batch mode execution without requiring columnstore indexes. It can also correct insufficient memory grants that cause expensive spills to disk. This adjustment can automatically correct excessive grants, which result in wasted memory and reduced concurrency. New feature or updateĮxpands on the batch mode memory grant feedback feature by adjusting memory grant sizes for both batch and row mode operators. ![]() ![]() Intelligent Query Processing is available by default on the latest database compatibility level setting, delivering broad impact that improves the performance of existing workloads with minimal implementation effort. At the same time, they remain adaptive to the constantly changing world of data. With Intelligent Query Processing, you know that critical parallel workloads improve when they're running at scale. From Intelligent Query Processing to support for persistent memory devices, the SQL Server Intelligent Database features improve performance and scalability of all your database workloads without any changes to your application or database design. SQL Server 2019 (15.x) builds on innovations in previous versions to provide industry-leading performance out of the box. Please refer to CREATE EXTERNAL DATA SOURCE for more information and samples.įor more information, see What are SQL Server Big Data Clusters?. SQL Server 2019 (15.x) Cumulative update 19 now introduces support for Oracle TNS files. For more information, see What is PolyBase?. Query data from external SQL Server, Oracle, Teradata, MongoDB, and ODBC data sources with external tables, now with UTF-8 encoding support. The SQL Server master instance provides high availability and disaster recovery for all databases by using Always On availability group technology. Use the data for AI, machine learning, and other analysis tasks.ĭeploy and run applications in Big Data Clusters. Query data from multiple external data sources through the cluster. Store big data in HDFS managed by SQL Server. Read, write, and process big data from Transact-SQL or Spark.Įasily combine and analyze high-value relational data with high-volume big data. New feature or updateĭeploy scalable clusters of SQL Server, Spark, and HDFS containers running on Kubernetes. ![]() Gain near real-time insights from all your data with SQL Server 2019 Big Data Clusters, which provide a complete environment for working with large sets of data, including machine learning and AI capabilities. Data virtualization and SQL Server 2019 Big Data Clustersīusinesses today often preside over vast data estates consisting of a wide array of ever-growing data sets that are hosted in siloed data sources across the company. The following sections provide an overview of these features.
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