HDInsight is a Hadoop distribution powered by the cloud. This means HDInsight was architected to handle any amount of data, scaling from terabytes to petabytes on demand. You can spin up any number of nodes at anytime. We charge only for the compute and storage you actually use.
Since it's 100% Apache Hadoop, HDInsight can process unstructured or semi-structured data from web clickstreams, social media, server logs, devices and sensors, and more. This allows you to analyze new sets of data which uncovers new business possibilities to drive your organization forward.
HDInsight has powerful programming extensions for languages including, C#, Java, .NET, and more. You can use your programming language of choice on Hadoop for the creation, configuration, submission, and monitoring of Hadoop jobs. See what else
With HDInsight, you can deploy Hadoop in the cloud without buying new hardware or other up-front costs. There’s also no time-consuming installation or set up. Azure does it for you. You can launch your first cluster in minutes.
Because it's integrated with Excel, HDInsight lets you visualize and analyze your Hadoop data in compelling new ways in a tool familiar to your business users. From Excel, users can select Azure HDInsight as a data source.
HDInsight is also integrated with Hortonworks Data Platform, so you can move Hadoop data from an on-site datacenter to the Azure cloud for backup, dev/test, and cloud bursting scenarios. Using the Microsoft Analytics Platform System, you can even query your on-premises and cloud-based Hadoop clusters at the same time.
This Hadoop ecosystem is a portfolio of fast-moving open source projects that are evolving quickly. To give customers flexibility, HDInsight has the option to deploy arbitrary Hadoop projects through custom scripts. This includes popular projects like Spark, R, Giraph and Solr.
HDInsight also includes Apache HBase, a columnar NoSQL database that runs on top of the Hadoop Distributed File System (HDFS). This allows you to do large transactional processing (OLTP) of nonrelational data enabling use cases like having interactive websites or sensor data write to Azure Blob storage.
HDInsight includes Apache Storm, an open-source stream analytics platform that can process real-time events at large scale. This allows you to do processing on millions of events as they are generated enabling use cases like Internet of Things (IoT) and gaining insights from your connected devices or web-triggered events. We make deploying and implementing Storm easier. See more details about Storm here.
HDInsight includes Apache Spark, an open source project in the Apache ecosystem that can run large-scale data analytic applications in-memory. This allows Spark to deliver up to 100x faster queries than traditional big data queries and a common execution model for various tasks like ETL, batch queries, interactive queries, real-time streaming, machine learning, and graph processing on data stored in Azure Storage.
Select Linux or Windows clusters when deploying Big Data workloads into Microsoft Azure. With Windows, leverage existing Windows based code, including .NET, to scale over all of your data in Azure. With Linux, customers can more easily move existing Hadoop workloads into the cloud and incorporate additional Big Data components which can run in the service. By offering choice for Windows and Linux clusters, Microsoft is enhancing flexibility for customers to create insight from the massive amounts of data being created in the cloud with the OS of their choice.
You might be surprised how easy it is to spin up a Hadoop cluster in the cloud. See for yourself. With 10 clicks or 20 minutes, you can create an HDInsight Hadoop cluster in the cloud. With HDInsight, you can even create multiple Hadoop clusters on the same set of data.
Click NEW on the lower left side, click DATA SERVICES, click HDINSIGHT and then click CUSTOM CREATE