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Azure Data Explorer

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Azure Data Explorer
Developer(s)Microsoft
Initial release2018; 7 years ago (2018)
PlatformMicrosoft Azure
TypeCloud storage
LicenseProprietary
Websitedocs.microsoft.com/en-us/azure/data-explorer/

Azure Data Explorer is a big data analytics cloud platform, developed by Microsoft, that ingests structured, semi-structured (like JSON) and unstructured data (like free-text)..[1]. The service then stores this data and answers analytic ad-hoc queries on it with seconds of latency.

It is offered as Platform as a Service (PaaS) as part of Microsoft Azure platform. The product was announced by Microsoft in 2018.

History

The development of the product began in 2014 as a grassroots incubation project in the Israeli R&D center of Microsoft[2], with the internal code name 'Kusto' (named after Jacques Cousteau, as a reference to "exploring the ocean of data"). The project aim was to address Azure services' needs for fast and scalable log and telemetry analytics. In 2016 it became the backend big-data and analytics service for Application Insights Analytics [3] The product was announced as a Public Preview product at the Microsoft Ignite 2018 conference[4] , and was announced as a general availability product at the Microsoft Ignite conference of February 2019[5]

Features

Azure Data Explorer offers an optimized query language (KQL - Keyword Query Language[6]. Previously know as Kusto Query Language.[7])[8]

Azure data Explorer can ingest 200MB per second per node[9]

Design

Azure Data Explorer is a distributed database running on a cluster of compute nodes in Microsoft Azure. It is based on relational database management systems (RDBMS), supporting entities such as databases, tables, and columns. It supports complex analytics query operators, such as calculated columns, searching and filtering or rows, group by-aggregates and joins.[10]

The engine service exposes a relational data model: At the top level (cluster) there is a collection of databases, each database contains a collection of tables and stored functions. Each table defines a schema (ordered list of typed fields).

In Azure Data Explorer, unlike a typical relational database management systems (RDBMS), there are no constraints like key uniqueness, primary and foreign key. The necessary relationships are established at the query time.[11]

References

  1. ^ orspod. "What is Azure Data Explorer?". docs.microsoft.com. Retrieved 2019-12-06.
  2. ^ "Microsoft R&D". www.microsoftrnd.co.il. Retrieved 2019-12-06.
  3. ^ orspod. "Introducing Application Insights Analytics". devblogs.microsoft.com. Retrieved 2019-12-06.
  4. ^ "Introducing Azure Data Explorer". azure.microsoft.com. Retrieved 2019-12-06.
  5. ^ "General Availability: Azure Data Explorer | Azure updates | Microsoft Azure". azure.microsoft.com. Retrieved 2019-12-06.
  6. ^ spdevdocs. "Keyword Query Language (KQL) syntax reference". docs.microsoft.com. Retrieved 2019-12-06.
  7. ^ "Getting Started with the Kusto Query Language (KQL) – System.Blog.Martens.Ben". blogs.msdn.microsoft.com. Retrieved 2019-12-06.
  8. ^ orspod. "What is Azure Data Explorer?". docs.microsoft.com. Retrieved 2019-12-06.
  9. ^ "Introducing Azure Data Explorer". azure.microsoft.com. Retrieved 2019-12-06.
  10. ^ orspod. "Getting started with Kusto - Azure Data Explorer". docs.microsoft.com. Retrieved 2019-12-06.
  11. ^ "Azure Data Explorer: a big data analytics cloud platform" (PDF).{{cite web}}: CS1 maint: url-status (link)
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