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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 .
Example of a database that can be used by a data lake (in this case structured data) A data lake is a system or repository of data stored in its natural/raw format, [1] usually object blobs or files. A data lake is usually a single store of data including raw copies of source system data, sensor data, social data etc., [2] and transformed data ...
Azure Data Lake is a scalable data storage and analytic service for big data analytics workloads that require developers to run massively parallel queries. 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 Cosmos DB is a globally distributed, multi-model database service offered by Microsoft.It is designed to provide high availability, scalability, and low-latency access to data for modern applications.
Dataverse is marketed for use with other Microsoft products such as Power Apps and Microsoft Dynamics 365 applications, and has data connectors to other Microsoft products like Azure Event Hub, Azure Service Bus, Microsoft SQL and Azure Data Lake. One example of use could be to use Dataverse as a form of data lake together with Microsoft Power ...
A data lake can contain structured data from relational databases, semi-structured data, unstructured data, and binary data. A data lake can be created on premises or in a cloud-based environment using the services from public cloud vendors such as Amazon , Microsoft , or Google .
Azure Data Explorer is a fully-managed [1] big data analytics cloud platform [2] [3] and data-exploration service, [4] developed by Microsoft, [5] [6] that ingests structured, semi-structured (like JSON) and unstructured data (like free-text).
Extract, load, transform (ELT) is an alternative to extract, transform, load (ETL) used with data lake implementations. In contrast to ETL, in ELT models the data is not transformed on entry to the data lake, but stored in its original raw format.