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Top 8 reasons to choose Azure HDInsight

Opublikowano: 18 czerwca, 2018

Senior Program Manager

Household names such as Adobe, Jet, ASOS, Schneider Electric, and Milliman are amongst hundreds of enterprises that are powering their Big Data Analytics using Azure HDInsight. Azure HDInsight launched nearly six years ago and has since become the best place to run Apache Hadoop and Spark analytics on Azure.

Here are the top eight reasons why enterprises are choosing Azure HDInsight for their big data applications:

1. Fully managed cluster service for Apache Hadoop and Spark workloads: Spin up Hive, Spark, LLAP, Kafka, HBase, Storm, or R Server clusters within minutes, deploy and run your applications and allow HDInsight do the rest. We will monitor the cluster and all the services, detect and repair common issues and respond to issues 24/7.

2. Guaranteed high availability (99.9 percent SLA) at large scale: Run your most critical and time sensitive workloads across thousands of cores and TBs of memory under the assurance of an industry-leading availability SLA of 99.9 percent for the whole software stack. Your big data applications can run more reliably as your HDInsight service monitors the health and automatically recovers from failures.

3. Industry-leading end to end security and compliance: Protect your most sensitive enterprise data assets using the full spectrum security technologies at your disposal. Isolate your HDInsight cluster within VNETs and take advantage of transparent data encryption. Develop rich role-based access policies using Apache Ranger and restrict access to your most critical data and applications. Achieve peace of mind knowing that your enterprise data assets are being handled and protected by a service that has received more than 30 industry standard certifications including ISO, SOC, HIPAA, PCI, and more.

4. Valuable applications available on Azure Marketplace: Pick from more than 30 popular Hadoop and Spark applications. Within several minutes, Azure HDInsight deploys the applications to the cluster.

5. Productive platform for analytics: Data engineers, data scientists and BI analysts can build their Hadoop/Spark applications using their favorite development tools (Visual Studio and Eclipse or IntelliJ), Notebooks (Jupyter or Zeppelin) languages (Scala, Python, R or C#) and frameworks (Java or .NET).

6. Enterprise-scale R for machine learning: Your data scientists can train more accurate models for better predictions in a shorter time by using Microsoft R Server for HDInsight. The multi-threaded math libraries and transparent parallelization in R Server provide the capability of handling up to thousands of more data and up to 50 times faster speed than open source R.

7. Global availability: Deployed in more than 26 public regions and multiple government clouds across the world, you will always find HDInsight in a data center near you.

8. High value for a low price: We know that cost is a very important consideration when running big data analytics. So, all the above value of Azure HDInsight is now available at half the price.

Get started

There is more to come as we prepare to bring the latest innovations in the Hadoop and Spark world to Azure HDInsight. You can read this developer guide and follow the quickstart section to learn more about implementing your big data applications on Azure HDInsight. Follow us on @AzureHDInsight or HDInsight blog for the latest updates. For questions and feedback, reach out to AskHDInsight@microsoft.com.