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Azure SQL Database includes built-in intelligence that learns app patterns and adapts them to maximize performance, reliability, and data protection. Key capabilities include: Learning of the host app's data access patterns, adaptive performance tuning, and automatic improvements to reliability and data protection.
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Azure Data Lake service was released on November 16, 2016. It is based on COSMOS, [2] which is used to store and process data for applications such as Azure, AdCenter, Bing, MSN, Skype and Windows Live.
Azure HDInsight [31] is a big data-relevant service that deploys Hortonworks Hadoop on Microsoft Azure and supports the creation of Hadoop clusters using Linux with Ubuntu. Azure Stream Analytics is a Serverless scalable event-processing engine that enables users to develop and run real-time analytics on multiple streams of data from sources ...
Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...
In Azure Data Explorer, unlike a typical relational database management systems (RDBMS), there are no constraints like key uniqueness, primary and foreign key. [26] The necessary relationships are established at the query time. [27] The data in Azure Data Explorer generally follows this pattern: [28] Creating Database, Ingesting data, Query the ...
Cosmos DB databases can be configured to be available in any of the Microsoft Azure regions (54 regions as of December 2018), letting application developers place their data closer to where their users are. [13] Each container's data gets transparently replicated across all configured regions.
Microsoft SQL Server Analysis Services (SSAS [1]) is an online analytical processing (OLAP) and data mining tool in Microsoft SQL Server.SSAS is used as a tool by organizations to analyze and make sense of information possibly spread out across multiple databases, or in disparate tables or files.