QueryIO vs Spark SQL comparison

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Comparison Buyer's Guide
Executive Summary

We performed a comparison between QueryIO and Spark SQL based on real PeerSpot user reviews.

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Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"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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"Offers a variety of methods to design queries and incorporates the regular SQL syntax within tasks.""The performance is one of the most important features. It has an API to process the data in a functional manner.""The solution is easy to understand if you have basic knowledge of SQL commands.""It is a stable solution.""The team members don't have to learn a new language and can implement complex tasks very easily using only SQL.""Spark SQL's efficiency in managing distributed data and its simplicity in expressing complex operations make it an essential part of our data pipeline.""Data validation and ease of use are the most valuable features.""The stability was fine. It behaved as expected."

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

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"Being a new user, I am not able to find out how to partition it correctly. I probably need more information or knowledge. In other database solutions, you can easily optimize all partitions. I haven't found a quicker way to do that in Spark SQL. It would be good if you don't need a partition here, and the system automatically partitions in the best way. They can also provide more educational resources for new users.""This solution could be improved by adding monitoring and integration for the EMR.""There should be better integration with other solutions.""In the next update, we'd like to see better performance for small points of data. It is possible but there are better tools that are faster and cheaper.""I've experienced some incompatibilities when using the Delta Lake format.""In the next release, maybe the visualization of some command-line features could be added.""It would be beneficial for aggregate functions to include a code block or toolbox that explains its calculations or supported conditional statements.""In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL."

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Pricing and Cost Advice
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  • "The solution is open-sourced and free."
  • "There is no license or subscription for this solution."
  • "The solution is bundled with Palantir Foundry at no extra charge."
  • "The on-premise solution is quite expensive in terms of hardware, setting up the cluster, memory, hardware and resources. It depends on the use case, but in our case with a shared cluster which is quite large, it is quite expensive."
  • "We use the open-source version, so we do not have direct support from Apache."
  • "We don't have to pay for licenses with this solution because we are working in a small market, and we rely on open-source because the budgets of projects are very small."
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    Top Answer:Spark SQL's efficiency in managing distributed data and its simplicity in expressing complex operations make it an essential part of our data pipeline.
    Top Answer:We don't have to pay for licenses with this solution because we are working in a small market, and we rely on open-source because the budgets of projects are very small.
    Top Answer:In terms of improvement, the only thing that could be enhanced is the stability aspect of Spark SQL. There could be additional features that I haven't explored but the current solution for working… more »
    Ranking
    16th
    out of 22 in Hadoop
    Views
    74
    Comparisons
    58
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    4th
    out of 22 in Hadoop
    Views
    1,569
    Comparisons
    1,005
    Reviews
    7
    Average Words per Review
    543
    Rating
    8.3
    Comparisons
    Learn More
    QueryIO
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    Overview
    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.
    Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure of both the data and the computation being performed. There are several ways to interact with Spark SQL including SQL and the Dataset API. When computing a result the same execution engine is used, independent of which API/language you are using to express the computation. This unification means that developers can easily switch back and forth between different APIs based on which provides the most natural way to express a given transformation.
    Sample Customers
    Information Not Available
    UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, Hitachi Solutions
    Top Industries
    No Data Available
    VISITORS READING REVIEWS
    Financial Services Firm21%
    Computer Software Company14%
    University8%
    Construction Company6%
    Company Size
    No Data Available
    REVIEWERS
    Small Business36%
    Midsize Enterprise43%
    Large Enterprise21%
    VISITORS READING REVIEWS
    Small Business13%
    Midsize Enterprise13%
    Large Enterprise74%
    Buyer's Guide
    Hadoop
    March 2024
    Find out what your peers are saying about Cloudera, Apache, Amazon and others in Hadoop. Updated: March 2024.
    765,234 professionals have used our research since 2012.

    QueryIO is ranked 16th in Hadoop while Spark SQL is ranked 4th in Hadoop with 14 reviews. QueryIO is rated 8.0, while Spark SQL is rated 7.8. The top reviewer of QueryIO writes "Stable with good connectivity and good integration capabilities". On the other hand, the top reviewer of Spark SQL writes "Offers the flexibility to handle large-scale data processing". QueryIO is most compared with Splice Machine, whereas Spark SQL is most compared with Apache Spark, IBM Db2 Big SQL, SAP HANA, HPE Ezmeral Data Fabric and Netezza Analytics.

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