Azure Data Lake allows developers, analysts, and data scientists to store huge data safety in the cloud. It also provides features for processing across languages and platforms. Microsoft says the solution removed complexities in mass data storage, allowing customers a faster and more efficient experience. The roll out in Europe includes both the company’s Azure Data Lake suites: Azure Data Lake Store – the first cloud Data Lake for enterprises that is secure, massively scalable and built to the open HDFS standard. With no limits to the size of data and the ability to run massively parallel analytics, you can now unlock value from all your unstructured, semi-structured and structured data. Azure Data Lake Analytics – the first cloud analytics job service where you can easily develop and run massively parallel data transformation and processing programs in U-SQL, R, Python and .NET over petabytes of data. It has rich built-in cognitive capabilities such as image tagging, emotion detection, face detection, deriving meaning from text, and sentiment analysis with the ability to extend to any type of analytics. With Azure Data Lake Analytics, there is no infrastructure to manage, and you can process data on demand, scale instantly, and only pay per job.
Azure Data Lake Store and Data Lake Analytics
Data Lake Analytics is a no-limit cloud data lake that was created specifically for enterprise customers in the cloud. It allows customers to analyse unstructured, semi-structured, and structured data. Microsoft built Azure Data Lake Store from the ground up. The purpose of the service it to offer massively parallel processing. It comes with SQL DW PolyBase integrated. ADLS gives customers the ability to load data directly into SQL DW at nearly three TB per hour. Last month, Microsoft introduced Data Lake Store Integration to Azure SQL DW. The new addition allows import and export data from Azure SQL DW directly to the lake store.
