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Microsoft SQL Server 2019 Standard

Can be activated inAll Countries

Windows

Companies that purchase Microsoft SQL Server 2019 Standard receive an extraordinarily efficient and high-performance database management software tailored to co...mpanies' needs. For the latest offspring of the software range, Microsoft relies on expanding numerous functions from the predecessor SQL Server 2017 and on innovations aimed at a further focus on topics such as machine learning, cloud applications, and big data. Another striking element is the fact that the software company SQL Server 2019 has included new connectors. This makes it easy to use SQL Server to query other databases. These include Teradata, MongoDB, Oracle and various generic ODBC data sources.

2514€

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Product Information

Language:Multilanguage
Users Supported:Unlimited
Dispatch:by E-mail
Manufacturer Part Number:228-11477
Term:Indefinite
Installations Supported:Unlimited
Year:2019
Supported Devices:Unlimited
Brand:Microsoft

System requirements

PlatformWindows, Linux, Mac
Processorx64 1.4 GHz CPU (minimum), x64 CPU 2.0 GHz or faster (recommended)
Hard diska minimum of 6 GB of available hard-disk space
Memory1 GB (minimum), 4 GB (recommended)
Supported Operating SystemWindows 10, Windows Server 2016, Windows Server 2019, Red Hat Enterprise Linux 7.3, Red Hat Enterprise Linux 7.4, SUSE Enterprise Linux Server v12 SP2, Ubuntu 16.04LTS, Docker Engine 1.8+

Microsoft SQL Server 2019 Standard

Microsoft SQL Server 2019 Standard – The solution for small businesses

Companies that purchase Microsoft SQL Server 2019 Standard receive an extraordinarily efficient and high-performance database management software tailored to companies' needs. For the latest offspring of the software range, Microsoft relies on expanding numerous functions from the predecessor SQL Server 2017 and on innovations aimed at a further focus on topics such as machine learning, cloud applications, and big data. Another striking element is the fact that the software company SQL Server 2019 has included new connectors. This makes it easy to use SQL Server to query other databases. These include Teradata, MongoDB, Oracle and various generic ODBC data sources.

Ideally equipped for big data with SQL Server 2019

Companies that purchase Microsoft SQL Server 2019 Standard are also prepared for extensive big data workloads. Microsoft integrates the two most important frameworks for big data - "Apache Spark", and the Hadoop Distributed File System (HDFS). Interoperability is provided thanks to the container orchestration software Kubernetes, while workloads can be executed locally and across various public clouds.

All in all, the software company from Redmond makes it much easier for users to work with large data volumes of up to 100 terabytes per database. Other new functions such as online transaction processing (OLTP) and data warehousing are also responsible. Besides, the PolyBase technology and the memory engine used have been revised. Thanks to the newly designed PolyBase technology, queries can now also be executed on the Azure Blob Storage or Hadoop data. The expansion of support for Hortonworks Hadoop clusters, Cloudera clusters, and Azure storage is also new.

Microsoft extends tried-and-tested functions

Companies that purchase Microsoft SQL Server 2019 Standard benefit from the fact that Microsoft is concentrating on the strengths of the predecessor version and consistently expanding it in the 2019 version. For example, Microsoft SQL Server 2019 Standard provides users with advanced diagram processing capabilities. No less attractive is the fact that the direct application of Java code is now also supported. The use of the same infrastructure as for Python and R code provides benefits for Machine Learning Services.

The most important new features of SQL Server 2019 at a glance

  • New connection of the Microsoft SQL Server 2019 Standard Edition with MongoDB, Teradata, Oracle and Co. and eliminate previous analysis barriers.
  • As a highly scaled service, Azure SQL DB Hyper-Scale enables automatic adaptation even to large workloads of up to 100 terabytes per database.
  • Vast expansion of the functions for diagram processing already known from the predecessor.
  • Direct execution of Java code, use of Python and R code for Machine Learning Services.
  • Revision of the PolyBase technology and the memory engine.
  • Integration of the two powerful big data frameworks Apache Spark and Hadoop Distributed File System (HDFS).
  • Execution of workloads both in a local environment and across multiple public clouds.

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