Amazon EMR vs QueryIO comparison

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Amazon Web Services (AWS) Logo
2,149 views|1,834 comparisons
85% willing to recommend
QueryIO Logo
73 views|56 comparisons
100% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Amazon EMR and QueryIO 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).
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Featured Review
Marco Reyes
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"In Amazon EMR it is easy to rebuild anything, easy to upgrade and has good fault tolerance.""It has a variety of options and support systems.""When we grade big jobs from on-prem to the cloud, we do it in EMR with Spark.""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.""The initial setup is pretty straightforward.""It allows users to access the data through a web interface.""The ability to resize the cluster is what really makes it stand out over other Hadoop and big data solutions.""Amazon EMR is a good solution that can be used to manage big data."

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"Anyone who has even a little bit of knowledge of the solution can begin to create things. You don't have to be technical to use the solution."

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Cons
"There is no need to pay extra for third-party software.""There is room for improvement in pricing.""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 legacy versions of the solution are not supported in the new versions.""The product must add some of the latest technologies to provide more flexibility to the users.""The dashboard management could be better. Right now, it's lacking a bit.""Modules and strategies should be better handled and notified early in advance.""Amazon EMR can improve by adding some features, such as megastore services and HiveServer2. Additionally, the user interface could be better, similar to what Apache service provides, cross-platform services."

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"There needs to be some simplification of the user interface."

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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."
  • More Amazon EMR 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 flexibility in managing user data.
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    Ranking
    3rd
    out of 22 in Hadoop
    Views
    2,149
    Comparisons
    1,834
    Reviews
    12
    Average Words per Review
    346
    Rating
    7.8
    16th
    out of 22 in Hadoop
    Views
    73
    Comparisons
    56
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Comparisons
    Also Known As
    Amazon Elastic MapReduce
    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.
    QueryIO is a Hadoop-based SQL and Big Data Analytics solution, used to store, structure, analyze and visualize vast amounts of structured and unstructured Big Data. It is especially well suited to enable users to process unstructured Big Data, give it a structure and support querying and analysis of this Big Data using standard SQL syntax. QueryIO enables you to leverage the vast and mature infrastructure built around SQL and relational databases and utilize it for your Big Data Analytics needs.
    Sample Customers
    Yelp
    Information Not Available
    Top Industries
    REVIEWERS
    Computer Software Company27%
    Media Company18%
    Wholesaler/Distributor18%
    Comms Service Provider9%
    VISITORS READING REVIEWS
    Financial Services Firm23%
    Computer Software Company13%
    Manufacturing Company8%
    Educational Organization6%
    No Data Available
    Company Size
    REVIEWERS
    Small Business26%
    Midsize Enterprise26%
    Large Enterprise47%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise12%
    Large Enterprise72%
    No Data Available
    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.
    768,578 professionals have used our research since 2012.

    Amazon EMR is ranked 3rd in Hadoop with 20 reviews while QueryIO is ranked 16th in Hadoop. Amazon EMR is rated 7.8, while QueryIO is rated 8.0. The top reviewer of Amazon EMR writes "Provides efficient data processing features and has good scalability ". On the other hand, the top reviewer of QueryIO writes "Stable with good connectivity and good integration capabilities". Amazon EMR is most compared with Snowflake, Cloudera Distribution for Hadoop, Azure Data Factory, Amazon Redshift and Apache Spark, whereas QueryIO is most compared with Splice Machine.

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    We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.