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HortonWorks Data Platform VS Microsoft HDInsight

Compare HortonWorks Data Platform VS Microsoft HDInsight and see what are their differences

HortonWorks Data Platform logo HortonWorks Data Platform

The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly...

Microsoft HDInsight logo Microsoft HDInsight

A managed Apache Hadoop, Spark, R, HBase, and Storm cloud service made easy
  • HortonWorks Data Platform Landing page
    Landing page //
    2023-09-28
  • Microsoft HDInsight Landing page
    Landing page //
    2023-04-10

HortonWorks Data Platform features and specs

  • Open Source Foundation
    HortonWorks Data Platform (HDP) is built entirely on open-source technologies, allowing for greater community support, flexibility, and transparency in its development and deployment.
  • Enterprise-Grade Security
    HDP offers robust security features, including authentication, authorization, auditing, and data protection, which are critical for managing sensitive data in enterprise environments.
  • Scalability
    The platform can handle large volumes of data, making it suitable for enterprises that require scalable solutions to manage their big data demands.
  • Comprehensive Ecosystem
    HortonWorks provides a comprehensive suite of tools and integrations, including Apache Hadoop, Hive, HBase, and others, enabling diverse data processing and analytics capabilities.

Possible disadvantages of HortonWorks Data Platform

  • Complexity
    The platform's extensive set of features and integrations can be complex to configure and manage, especially for organizations without dedicated data engineering teams.
  • Resource Intensiveness
    Running HDP can be resource-intensive, requiring significant hardware and infrastructure investments, which might be a barrier for smaller organizations.
  • Learning Curve
    Due to its complexity and the breadth of technologies involved, there is a steep learning curve for new users or teams unfamiliar with the Hadoop ecosystem.
  • Support and Documentation
    While there is community support available due to its open-source nature, some users might find official support and comprehensive documentation lacking compared to proprietary solutions.

Microsoft HDInsight features and specs

  • Scalability
    HDInsight allows users to scale their big data clusters up or down according to the workload demands, making it flexible for various data processing needs.
  • Integration
    Seamlessly integrates with other Azure services, such as Azure Storage, Azure Data Lake, and Azure Machine Learning, enabling comprehensive data processing and analytics solutions.
  • Support for Open-Source Frameworks
    Supports a range of open-source frameworks, including Hadoop, Spark, Hive, and MapReduce, allowing users to leverage existing tools and expertise.
  • Security Features
    Includes enterprise-grade security with features such as network isolation, encryption, and integration with Azure Active Directory for access management.
  • Cost Efficiency
    Offers cost-effective pricing models, such as pay-as-you-go and reserved pricing, helping organizations manage their budgets efficiently.

Possible disadvantages of Microsoft HDInsight

  • Complexity
    Setting up and managing clusters can be complex and may require specialized knowledge, which could be a barrier for smaller teams without dedicated IT staff.
  • Performance Overhead
    Virtualized environments may introduce performance overheads compared to running big data solutions on bare metal.
  • Dependency on Azure Ecosystem
    Being a part of Azure, HDInsight's effectiveness is maximized when used with other Azure services, potentially leading to dependency on the Azure ecosystem.
  • Limited Customization
    HDInsight offers less customization compared to deploying and managing open-source frameworks on dedicated infrastructure, which might be limiting for some use cases.
  • Cost Variability
    While there are cost-effective pricing models, unforeseen spikes in data processing can lead to variable and sometimes high costs.

HortonWorks Data Platform videos

Why You Need Hortonworks Data Platform 3.0

More videos:

  • Review - Hortonworks Data Platform 3.0 – Faster, Smarter, Hybrid Data

Microsoft HDInsight videos

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Category Popularity

0-100% (relative to HortonWorks Data Platform and Microsoft HDInsight)
Data Dashboard
67 67%
33% 33
Big Data
84 84%
16% 16
Development
59 59%
41% 41
Data Warehousing
100 100%
0% 0

User comments

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Social recommendations and mentions

Microsoft HDInsight might be a bit more popular than HortonWorks Data Platform. We know about 1 link to it since March 2021 and only 1 link to HortonWorks Data Platform. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

HortonWorks Data Platform mentions (1)

Microsoft HDInsight mentions (1)

  • What are some options for a server version of R?
    I also know that Microsoft used to as well with Microsoft Machine Learning Server, but I read their blog post update on deprecating that next year and, honestly still find it confusing--like, are they still having an R server option or is it just R integration into other server-based services? What is this "R Server for HDInsight" thing? Source: over 3 years ago
  • Is azure a viable career path for DE?
    Also there is HDInsight: https://azure.microsoft.com/en-us/services/hdinsight/. Source: almost 4 years ago

What are some alternatives?

When comparing HortonWorks Data Platform and Microsoft HDInsight, you can also consider the following products

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost

IBM SPSS Statistics - IBM SPSS Statistics is software that provides detailed analysis of statistical data. The company behind the product practically needs no introduction, as it's been a staple of the technology industry for over 100 years.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

JMP - JMP is a data representation tool that empowers the engineers, mathematicians and scientists to explore the any of data visually.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?