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Data Lake Storage Gen2 Preview is available in the West US 2 and West Central US regions. During the preview, usage charges will show as "ADFS" on invoices. Names will change starting September 1, 2018.
Azure Data Lake Storage Gen2 is a highly scalable, performant, and cost-effective data lake solution for big data analytics.
We’re announcing several new capabilities across a wide range of OSS frameworks and support of Azure Data Lake Storage Gen2 on Azure HDInsight.
Azure Data Lake Storage Gen2 offers a no-compromise data lake. It unifies the core capabilities from the first generation of Azure Data Lake with a Hadoop compatible file system endpoint now directly integrated into Azure Blob Storage. This enhancement combines the scale and cost benefits of object storage with the reliability and performance typically associated only with on-premises file systems. This new file system includes a full hierarchical namespace that makes files and folders first class citizens, translating to faster, more reliable analytic job execution.
Azure Databricks is a high-performance Apache Spark-based platform optimized for Azure.
New updates to Azure IoT Remote Monitoring, a solution accelerator that's fully operational right out of the box, are now available.
Azure Data Lake Analytics can help you easily organize, manage, and gain insights from Data Lake Analytics jobs that are running as part of pipelines or on a recurring basis.
Implement your organization's policies to ensure that compute resources (AUs) are always available for your most critical U-SQL jobs.
The Azure Stream Analytics team is happy to announce that we just released three updates to the Azure portal (https://portal.azure.com/).
Azure Data Lake updates are available and provide basic improvements across the board.
You can use Azure Data Factory to move data to and from Data Lake Store, and you can run queries with Data Lake Analytics.
Azure Data Lake Store provides a single repository where you can simply capture data of any size, type, and speed—without forcing changes to your application as the data scales.
Azure Data Lake Analytics dynamically scales so you can focus on your business goals. Instead of deploying, configuring, and tuning hardware, you write queries to transform your data and help extract valuable insights.