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  2. Microsoft Azure SQL Database - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Azure_SQL_Database

    Azure SQL Database supports multi-modal storage of structured, semi-structured, and non-relational data. [2] Azure SQL Database includes built-in intelligence that learns app patterns and adapts them to maximize performance, reliability, and data protection. Key capabilities include:

  3. Common warehouse metamodel - Wikipedia

    en.wikipedia.org/wiki/Common_Warehouse_Metamodel

    The common warehouse metamodel (CWM) defines a specification for modeling metadata for relational, non-relational, multi-dimensional, and most other objects found in a data warehousing environment. The specification is released and owned by the Object Management Group , which also claims a trademark in the use of "CWM".

  4. Azure Data Explorer - Wikipedia

    en.wikipedia.org/wiki/Azure_Data_Explorer

    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 ...

  5. Online analytical processing - Wikipedia

    en.wikipedia.org/wiki/Online_analytical_processing

    It can ingest data from offline data sources (such as Hadoop and flat files) as well as online sources (such as Kafka). Pinot is designed to scale horizontally. Mondrian OLAP server is an open-source OLAP server written in Java. It supports the MDX query language, the XML for Analysis and the olap4j interface specifications.

  6. Data warehouse - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse

    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 ...

  7. Data warehouse automation - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse_automation

    Data warehouse automation (DWA) refers to the process of accelerating and automating the data warehouse development cycles, while assuring quality and consistency. DWA is believed to provide automation of the entire lifecycle of a data warehouse, from source system analysis to testing to documentation .

  8. Data access layer - Wikipedia

    en.wikipedia.org/wiki/Data_access_layer

    If the data access layer supports multiple database types, the application becomes able to use whatever databases the DAL can talk to. In either circumstance, having a data access layer provides a centralized location for all calls into the database, and thus makes it easier to port the application to other database systems (assuming that 100% ...

  9. Web API - Wikipedia

    en.wikipedia.org/wiki/Web_API

    An example of a popular web API is the Astronomy Picture of the Day API operated by the American space agency NASA. It is a server-side API used to retrieve photographs of space or other images of interest to astronomers, and metadata about the images. According to the API documentation, [15] the API has one endpoint:

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