Amazon EMR vs Apache Spark vs Hortonworks Data Platform comparison

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Amazon Web Services (AWS) Logo
2,108 views|1,795 comparisons
85% willing to recommend
Apache Logo
2,430 views|1,869 comparisons
89% willing to recommend
Cloudera Logo
606 views|352 comparisons
89% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Amazon EMR, Apache Spark, and Hortonworks Data Platform based on real PeerSpot user reviews.

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.
To learn more, read our detailed Hadoop Report (Updated: April 2024).
770,292 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"It has a variety of options and support systems.""One of the valuable features about this solution is that it's managed services, so it's pretty stable, and scalable as much as you wish. It has all the necessary distributions. With some additional work, it's also possible to change to a Spark version with the latest version of EMR. It also has Hudi, so we are leveraging Apache Hudi on EMR for change data capture, so then it comes out-of-the-box in EMR.""Amazon EMR is a good solution that can be used to manage big data.""Amazon EMR's most valuable features are processing speed and data storage capacity.""The project management is very streamlined.""The ability to resize the cluster is what really makes it stand out over other Hadoop and big data solutions.""The solution is pretty simple to set up.""We are using applications, such as Splunk, Livy, Hadoop, and Spark. We are using all of these applications in Amazon EMR and they're helping us a lot."

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"The most valuable feature of Apache Spark is its ease of use.""The main feature that we find valuable is that it is very fast.""One of Apache Spark's most valuable features is that it supports in-memory processing, the execution of jobs compared to traditional tools is very fast.""Provides a lot of good documentation compared to other solutions.""Apache Spark provides a very high-quality implementation of distributed data processing.""The fault tolerant feature is provided.""There's a lot of functionality.""The product's deployment phase is easy."

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"Ranger for security; with Ranger we can manager user’s permissions/access controls very easily.""Now, using this solution, it is much cheaper to have all of the data available for searching, not in real-time, but whenever there is a pending request.""The data platform is pretty neat. The workflow is also really good.""The Hortonworks solution is so stable. It is working as a production system, without any error, without any downtime. If I have downtime, it is mostly caused by the hardware of the computers.""The scalability is the key reason why we are on this platform.""The upgrades and patches must come from Hortonworks.""Distributed computing, secure containerization, and governance capabilities are the most valuable features.""The product offers a fairly easy setup process."

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Cons
"There is room for improvement in pricing.""Modules and strategies should be better handled and notified early in advance.""We don't have much control. If we have multiple users, if they want to scale up, the cost will go and increase and we don't know how we can restrict that price part.""The initial setup was time-consuming.""The problem for us is it starts very slow.""The product must add some of the latest technologies to provide more flexibility to the users.""The most complicated thing is configuring to the cluster and ensure it's running correctly.""Amazon EMR is continuously improving, but maybe something like CI/CD out-of-the-box or integration with Prometheus Grafana."

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"Spark could be improved by adding support for other open-source storage layers than Delta Lake.""I know there is always discussion about which language to write applications in and some people do love Scala. However, I don't like it.""Apache Spark can improve the use case scenarios from the website. There is not any information on how you can use the solution across the relational databases toward multiple databases.""When you are working with large, complex tasks, the garbage collection process is slow and affects performance.""It's not easy to install.""When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources.""The logging for the observability platform could be better.""The setup I worked on was really complex."

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"It's at end of life and no longer will there be improvements.""The cost of the solution is high and there is room for improvement.""It would also be nice if there were less coding involved.""More information could be there to simplify the process of running the product.""Hive performance. If Hive performance increased, Hadoop would replace (not everywhere) traditional databases.""The version control of the software is also an issue.""Security and workload management need improvement.""I work a lot with banking, IT and communications customers. Hortonworks must improve or must upgrade their services for these sectors."

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Pricing and Cost Advice
  • "You don't need to pay for licensing on a yearly or monthly basis, you only pay for what you use, in terms of underlying instances."
  • "The cost of Amazon EMR is very high."
  • "The price of the solution is expensive."
  • "Amazon EMR's price is reasonable."
  • "There is a small fee for the EMR system, but major cost components are the underlying infrastructure resources which we actually use."
  • "There is no need to pay extra for third-party software."
  • "Amazon EMR is not very expensive."
  • "The product is not cheap, but it is not expensive."
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  • "Since we are using the Apache Spark version, not the data bricks version, it is an Apache license version, the support and resolution of the bug are actually late or delayed. The Apache license is free."
  • "Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
  • "We are using the free version of the solution."
  • "Apache Spark is not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."
  • "Apache Spark is an expensive solution."
  • "Spark is an open-source solution, so there are no licensing costs."
  • "On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
  • "It is an open-source solution, it is free of charge."
  • More Apache Spark Pricing and Cost Advice →

  • "It is priced well and it is affordable"
  • "Currently, we are using the product in a sandbox environment, and there is no licensing. We might choose a licensing option once we get the results."
  • More Hortonworks Data Platform Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Amazon EMR is a good solution that can be used to manage big data.
    Top Answer:As people are shifting from legacy solutions to other technologies, Amazon EMR needs to add more features that give more… more »
    Top Answer:We use Spark to process data from different data sources.
    Top Answer:In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond… more »
    Top Answer:Distributed computing, secure containerization, and governance capabilities are the most valuable features.
    Top Answer:I haven't done a price analysis specifically for HDP. However, when it was first introduced as Hadoop 2.0, there were a… more »
    Top Answer:Since Cloudera acquired HDP, it's been bundled with CBH and HDP. However, the biggest challenge is cloud storage… more »
    Ranking
    3rd
    out of 22 in Hadoop
    Views
    2,108
    Comparisons
    1,795
    Reviews
    12
    Average Words per Review
    346
    Rating
    7.8
    1st
    out of 22 in Hadoop
    Views
    2,430
    Comparisons
    1,869
    Reviews
    26
    Average Words per Review
    444
    Rating
    8.7
    6th
    out of 22 in Hadoop
    Views
    606
    Comparisons
    352
    Reviews
    5
    Average Words per Review
    354
    Rating
    8.0
    Comparisons
    Also Known As
    Amazon Elastic MapReduce
    Hortonworks, HDP
    Learn More
    Overview
    Amazon Elastic MapReduce (Amazon EMR) is a web service that makes it easy to quickly and cost-effectively process vast amounts of data. Amazon EMR simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective for you to distribute and process vast amounts of your data across dynamically scalable Amazon EC2 instances.

    Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

    Hortonworks is a leading innovator in the industry, creating, distributing and supporting enterprise-ready open data platforms and modern data applications. Our mission is to manage the world's data. We have a single-minded focus on driving innovation in open source communities such as Apache Hadoop, NiFi, and Spark. We along with our 1600+ partners provide the expertise, training and services that allow our customers to unlock transformational value for their organizations across any line of business. Our connected data platforms powers modern data applications that deliver actionable intelligence from all data: data-in-motion and data-at-rest. We are Powering the Future of Data.
    Sample Customers
    Yelp
    NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
    Mayo Clinic, Symantec, Progressive Insurance, Noble Energy, Cardinal Health, Rogers, Mercy, Neustar, TRUECar, T-Mobile
    Top Industries
    REVIEWERS
    Computer Software Company27%
    Wholesaler/Distributor18%
    Media Company18%
    Comms Service Provider9%
    VISITORS READING REVIEWS
    Financial Services Firm23%
    Computer Software Company13%
    Manufacturing Company8%
    Educational Organization6%
    REVIEWERS
    Computer Software Company30%
    Financial Services Firm15%
    University9%
    Marketing Services Firm6%
    VISITORS READING REVIEWS
    Financial Services Firm25%
    Computer Software Company13%
    Manufacturing Company7%
    Comms Service Provider6%
    REVIEWERS
    Comms Service Provider30%
    Manufacturing Company10%
    Government10%
    Financial Services Firm10%
    VISITORS READING REVIEWS
    Computer Software Company19%
    Financial Services Firm15%
    Comms Service Provider6%
    Outsourcing Company6%
    Company Size
    REVIEWERS
    Small Business26%
    Midsize Enterprise26%
    Large Enterprise47%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise11%
    Large Enterprise72%
    REVIEWERS
    Small Business40%
    Midsize Enterprise18%
    Large Enterprise42%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise12%
    Large Enterprise71%
    REVIEWERS
    Small Business25%
    Midsize Enterprise18%
    Large Enterprise57%
    VISITORS READING REVIEWS
    Small Business26%
    Midsize Enterprise13%
    Large Enterprise61%
    Buyer's Guide
    Hadoop
    April 2024
    Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop. Updated: April 2024.
    770,292 professionals have used our research since 2012.