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Azure updates

Learn about important Azure product updates, roadmap, and announcements. Subscribe to notifications to stay informed.

Products

    February 2019

    Feb 7

    Azure Data Lake Storage Gen2 is now generally available

    Azure Data Lake Storage Gen2 is a no-compromises data lake platform that combines the rich feature set of advanced data lake solutions with the economics, global scale, and enterprise grade security of Azure Blob Storage.

    November 2018

    Nov 14

    Azure Event Hubs for Apache Kafka is now available

    With Azure Event Hubs for Apache Kafka, we’re bringing together two powerful distributed streaming platforms so you can access the breadth of Kafka ecosystem applications without having to manage servers or networks.

    July 2018

    Jul 19

    Azure Data Lake Storage Gen2 name change

    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.

    June 2018

    Jun 27

    Azure Data Lake Storage Gen2 now in preview

    Azure Data Lake Storage Gen2 is a highly scalable, performant, and cost-effective data lake solution for big data analytics.

    Jun 27

    Updates to Hadoop, Spark, and Data Lake Storage Gen2 on Azure HDInsight

    We’re announcing several new capabilities across a wide range of OSS frameworks and support of Azure Data Lake Storage Gen2 on Azure HDInsight.

    Jun 27

    Announcing the preview for Azure Data Lake Storage Gen2

    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.

    November 2017

    Nov 17

    Azure Databricks

    Azure Databricks is a high-performance Apache Spark-based platform optimized for Azure.

    October 2017

    Oct 15

    Azure IoT Remote Monitoring update

    New updates to Azure IoT Remote Monitoring, a solution accelerator that's fully operational right out of the box, are now available.

    Oct 2

    Azure Data Lake Analytics introduces capabilities to manage pipelines and recurring jobs

    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.

    July 2017

    Jul 18

    Azure Data Lake Analytics now supports new policies to manage compute resources (AUs)

    Implement your organization's policies to ensure that compute resources (AUs) are always available for your most critical U-SQL jobs.

    July 2016

    Jul 19

    General availability: Azure portal updates for Azure Stream Analytics

    The Azure Stream Analytics team is happy to announce that we just released three updates to the Azure portal (https://portal.azure.com/).

    May 2016

    May 13

    Azure Data Lake update announcement

    Azure Data Lake updates are available and provide basic improvements across the board.

    November 2015

    Nov 18

    Azure Data Lake Store and Azure Data Lake Analytics integration with Azure Data Factory

    You can use Azure Data Factory to move data to and from Data Lake Store, and you can run queries with Data Lake Analytics.

    October 2015

    Oct 29

    Public preview: Azure Data Lake Store

    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.

    Oct 29

    Public preview: Azure Data Lake Analytics

    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.

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