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Applies to:
SQL Server
Microsoft SQL Server is a relational database management system (RDBMS). Applications and tools connect to a SQL Server instance or database, and communicate using Transact-SQL (T-SQL).
You can install SQL Server on Windows or Linux, deploy it in a Linux container, or deploy it on an Azure Virtual Machine or other virtual machine platform. You previously might have referred to this as the boxed product.
Supported versions of SQL Server depend on your license agreement, but for the purposes of this documentation, we mean SQL Server 2016 (13.x) and later versions. Documentation for SQL Server 2014 (12.x) and previous versions is available at Previous versions of SQL Server documentation. To find out which versions of SQL Server are currently supported, see SQL Server end of support options.
The underlying SQL Server Database Engine is also used by the following products and services:
For a list of features supported by the editions of SQL Server on Windows, see:
This section describes some of the key technologies available in SQL Server.
Component | Description |
---|---|
Database Engine | The Database Engine is the core service for storing, processing, and securing data. The Database Engine provides controlled access and transaction processing to meet the requirements of the most demanding data consuming applications within your enterprise. The Database Engine also provides rich support for sustaining business continuity through Business continuity and database recovery - SQL Server. |
Machine Learning Services (MLS) | SQL Server Machine Learning Services supports integration of machine learning, using the popular R and Python languages, into enterprise workflows. Machine Learning Services (In-Database) integrates R and Python with SQL Server, making it easy to build, retrain, and score models by calling stored procedures. Machine Learning Server provides enterprise-scale support for R and Python, without requiring SQL Server. |
Integration Services (SSIS) | SQL Server Integration Services is a platform for building high performance data integration solutions, including packages that provide extract, transform, and load (ETL) processing for data warehousing. |
Analysis Services (SSAS) | SQL Server Analysis Services is an analytical data platform and toolset for personal, team, and corporate business intelligence. Servers and client designers support traditional OLAP solutions, new tabular modeling solutions, as well as self-service analytics and collaboration using Power Pivot, Excel, and a SharePoint Server environment. Analysis Services also includes Data Mining so that you can uncover the patterns and relationships hidden inside large volumes of data. |
Reporting Services (SSRS) | SQL Server Reporting Services delivers enterprise, Web-enabled reporting functionality. You can create reports that draw content from various data sources, publish reports in various formats, and centrally manage security and subscriptions. |
Replication | SQL Server Replication is a set of technologies for copying and distributing data and database objects from one database to another, and then synchronizing between databases to maintain consistency. By using replication, you can distribute data to different locations and to remote or mobile users with local and wide area networks, dial-up connections, wireless connections, and the Internet. |
Data Quality Services (DQS) | Data Quality Services provides you with a knowledge-driven data cleansing solution. DQS enables you to build a knowledge base, and then use that knowledge base to perform data correction and deduplication on your data, using both computer-assisted and interactive means. You can use cloud-based reference data services, and you can build a data management solution that integrates DQS with SQL Server Integration Services and Master Data Services. |
Master Data Services (MDS) | Master Data Services is the SQL Server solution for master data management. A solution built on Master Data Services helps ensure that reporting and analysis are based on the right information. Using Master Data Services, you create a central repository for your master data and maintain an auditable, securable record of that data as it changes over time. |
This table provides links to fundamental concepts in SQL Server and Azure SQL.
Although SQL Server is a standalone product, which can be installed on computers running Windows and Linux operating systems, you can integrate your SQL Server instances with several Azure services.
SQL Server on Azure Virtual Machines enables you to use full versions of SQL Server in the cloud without having to manage any on-premises hardware. SQL Server virtual machines (VMs) also simplify licensing costs when you pay as you go.
Azure virtual machines run in many different geographic regions around the world. They also offer various machine sizes. The virtual machine image gallery allows you to create a SQL Server VM with the right version, edition, and operating system. This makes virtual machines a good option for many different SQL Server workloads.
SQL Server enabled by Azure Arc simplifies governance and management by delivering a consistent multicloud and on-premises management platform. Azure Arc provides a centralized, unified way to manage your entire environment together, combining existing non-Azure and/or on-premises virtual machines, Kubernetes clusters, and databases into Azure Resource Manager.
You can use Azure services and management capabilities, introduce DevOps practices to support new cloud native patterns in your environment, and configure custom locations as an abstraction layer on top of Azure Arc-enabled Kubernetes clusters and cluster extensions, regardless of where your resources live.
Azure Kubernetes Service (AKS) is a managed Kubernetes service for deploying and managing container clusters. With SQL Server on Linux containers, you can deploy a SQL Server Linux container to AKS using Helm charts.
Notitie
You can also set up SQL Managed Instance enabled by Azure Arc on a Kubernetes infrastructure of your choice, which allows you to manage the service in Azure while your data stays in the location you prefer.
SQL Server provides many opportunities to migrate and modernize your data estate.
1 SQL Server 2017 (14.x) and later versions.
Did you know that you can edit SQL content yourself? If you do so, not only do you help improve our documentation, but you also get credited as a contributor to the page.
For more information, see How to contribute to SQL Server documentation
gebeurtenis
31 mrt, 23 - 2 apr, 23
De grootste SQL-, Fabric- en Power BI-leerevenement. 31 maart – 2 april. Gebruik code FABINSIDER om $ 400 te besparen.
Zorg dat u zich vandaag nog registreertTraining
Leertraject
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Certificering
Microsoft Certified: Azure Database Administrator Associate - Certifications
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Documentatie
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