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  2. Databricks - Wikipedia

    en.wikipedia.org/wiki/Databricks

    Databricks develops and sells a cloud data platform using the marketing term "lakehouse", a portmanteau of "data warehouse" and "data lake". [41] Databricks' Lakehouse is based on the open-source Apache Spark framework that allows analytical queries against semi-structured data without a traditional database schema. [42]

  3. Databricks makes bringing data into its 'lakehouse' easier - AOL

    www.aol.com/news/databricks-makes-bringing-data...

    Databricks today announced the launch of its new Data Ingestion Network of partners and the launch of its Databricks Ingest service. At the core of the company's lakehouse is Delta Lake ...

  4. Azure Data Lake - Wikipedia

    en.wikipedia.org/wiki/Azure_Data_Lake

    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. COSMOS features a SQL-like query engine called SCOPE upon which U-SQL was built. [2]

  5. Data lake - Wikipedia

    en.wikipedia.org/wiki/Data_lake

    [14] [15] A data lakehouse architecture attempts to address several criticisms of data lakes by adding data warehouse capabilities such as transaction support, schema enforcement, governance, and support for diverse workloads. According to Oracle, data lakehouses combine the "flexible storage of unstructured data from a data lake and the ...

  6. Synthetic monitoring - Wikipedia

    en.wikipedia.org/wiki/Synthetic_monitoring

    Datadog's Automated Synthetic Monitoring; Powerhouse Nudge Synthetic Monitoring by Atakama Technologies; Alyvix's visual synthetic monitoring for applications and services; By implementing Synthetic Monitoring IT/Operations staffs are able to identify application issues in advance of them becoming critical, and take remedial action.

  7. Azure Data Explorer - Wikipedia

    en.wikipedia.org/wiki/Azure_Data_Explorer

    Azure Data Explorer can ingest 200 MB per second per node. [14] Data Ingestion methods are pipelines and connectors to common services like Azure Event Grid or Azure Event Hub, [21] or programmatic ingestion using SDKs. Data visualization can be achieved using their native dashboard offering, or with tools like Power BI [21] [22] or Grafana ...

  8. 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]

  9. Azure Stream Analytics - Wikipedia

    en.wikipedia.org/wiki/Azure_Stream_Analytics

    azure.microsoft.com /en-us /services /stream-analytics / Microsoft Azure Stream Analytics is a serverless scalable complex event processing engine by Microsoft that enables users to develop and run real-time analytics on multiple streams of data from sources such as devices, sensors, web sites, social media, and other applications. [ 1 ]

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