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What is Data Lake and Azure Data Lake

What is data lake ?
A data lake is a storage repository that holds a vast amount of raw data in its native format until it is needed. While a hierarchical data warehouse stores data in files or folders, a data lake uses a flat architecture to store data. Each data element in a lake is assigned a unique identifier and tagged with a set of extended metadata tags. When a business question arises, the data lake can be queried for relevant data, and that smaller set of data can then be analyzed to help answer the question.

A data lake, on the other hand, maintains data in their native formats and handles the three Vs of big data — volume, velocity, and variety — while providing tools for analyzing, querying, and processing. Data lakes eliminate all the restrictions of a typical data warehouse system by providing unlimited space, unrestricted file size, schema on read, and various ways to access data (including programming, SQL-like queries, and REST calls).

What is Azure Data Lake ?
Azure Data Lake is a Bigdata and data-warehouse platform on azure cloud. It is a highly scalable public cloud service that allows developers, scientists, business professionals and other Microsoft customers to gain insight from large, complex data sets. As with most data lake offerings, the service is composed of two parts: data storage and data analytics.

The Azure Data Lake service was released on November 16th, 2016. Azure Data Lake is built on the learnings and technologies of COSMOS, Microsoft’s internal big data system. COSMOS 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.

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