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Azure HDInsight

Azure HDInsight

Overview

What is Azure HDInsight?

HDInsight is an implementation of the Apache Hadoop technology stack on the Microsoft Azure cloud platform: It is based on the Hortonworks Hadoop distribution. Microsoft Azure HDInsight includes implementations of Apache Spark, HBase, Storm, Pig, Hive, Sqoop, Oozie, Ambari, etc.…

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Recent Reviews

totally friendly!

9 out of 10
November 09, 2020
Incentivized
Azure HDInsight is being used across the whole organization in 3 countries that work together. The solution is that the organization pay …
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Reviewer Pros & Cons

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Product Demos

Demo Azure HDInsight auf Linux

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Using semi structured data like JSON with Hive on Azure HDInsight

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Drive higher utilization of Azure HDInsight clusters with Autoscale | Data Exposed

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Fine-grained security with Apache Ranger on HDInsight Kafka | Azure Friday

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HDInsight: Fast Interactive Queries with Hive on LLAP | Azure Friday

YouTube
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Product Details

What is Azure HDInsight?

HDInsight is an implementation of the Apache Hadoop technology stack on the Microsoft Azure cloud platform: It is based on the Hortonworks Hadoop distribution.

Microsoft Azure HDInsight includes implementations of Apache Spark, HBase, Storm, Pig, Hive, Sqoop, Oozie, Ambari, etc. It also integrates with with business intelligence (BI) tools such as Power BI, Excel, SQL Server Analysis Services, and SQL Server Reporting Services.

Azure HDInsight Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo
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Comparisons

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Reviews and Ratings

(36)

Attribute Ratings

Reviews

(1-6 of 6)
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Score 4 out of 10
Vetted Review
Verified User
Incentivized
  • When our business started, it was a great value for a company with no tech experts
  • When business grow and data volumes also, problems started to arise: lots of on-demand clusters creations failed, cluster internal cluster crashed due to logs size (no way to limit them)
  • When business got really big, after having months of outage, we have to start looking for a new platform. It became ineffective in ROI.
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