What users are saying about

Apache Spark

99 Ratings
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Score 8.6 out of 101

Hortonworks Data Platform

33 Ratings
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Score 8.6 out of 101

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Likelihood to Recommend

Apache Spark

Spark is great as a workflow process and extract transform layer process tool. Is really good for machine learning especially for large datasets that can be processed in split file paralallelization. Spark streaming is scalable for close to real-time data workflow process.what it's not good for, is smaller subset of data processing.
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Hortonworks Data Platform

I find HDP easy to use and solves most of the problems for people looking to manage their big data. Evaluating the Hortonworks Data Platform is easy as it is free to download and install in your cluster. Single node cluster available as Sandbox is also easy for POCs.
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Pros

  • Machine Learning.
  • Data Analysis
  • WorkFlow process (faster than MapReduce).
  • SQL connector to multiple data sources
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  • HDP keeps up-to pace with the Apache Hadoop.
  • HDP's Ambari is intuitive and easy to use.
  • HDP remains similar to most open source tools and hence makes the learning curve gentler.
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Cons

  • Debugging is difficult as it is new for most people
  • There are fewer learning resources
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  • The HDP community is relatively new and could get better.
  • Tools like Falcon which are not so much used in general tend to remain dormant in the HDP when it comes to development.
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Implementation

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Hortonworks Data Platform9.0
Based on 1 answer
Try not to change variable names.
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Alternatives Considered

Even with Python, MapReduce is lengthy coding. Combination of Python with Apache Spark will not only shorten the code, but it will effectively increase the speed of algorithms. Occasionally, I use MapReduce, but Apache Spark will replace MapReduce very soon. It has many built-in and faster features.
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While Apache Hadoop is completely open sourced, Hortonworks Data Platform offers support as well as keeps pace with the open source versions. Also, the HDP open sources its own products, thus giving back to the community. I find using the Hortonworks Data Platform more intuitive than Cloudera or MapR versions.
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Return on Investment

  • By learning Spark, we can become certified and/or provide proper recommendations or implementations on Spark solutions.
  • With a background in Hadoop distributed processes, it has been easy to understand and diagnose how Spark handles the transfer of data within a cluster. Especially when using YARN as the resource manager and HDFS as the data source.
  • Staying up to date with the latest changes to Spark has become a repetitive task. While most Hadoop distributions only support Spark 1.6 at the moment, Spark 2.0 has introduced some useful features, but those require a re-write of existing applications.
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  • We have developed a strong partnership with Hortonworks.
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Pricing Details

Apache Spark

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Hortonworks Data Platform

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details