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Altiscale vs Spark SQL comparison

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Altiscale

25 views|9 comparisons
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Spark SQL

Read 14 Spark SQL reviews
1,534 views|1,005 comparisons
85% willing to recommend
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Buyer's Guide
Hadoop
April 2024
Executive Summary

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

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.
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Featured Review
Use Altiscale?
Lucas Dreyer
Processing solution used for data engineering and transformation with the ability to process large datasets
Certain data sets that are very large are very difficult to process with Pandas and Python libraries. Spark SQL has helped us a lot with that.
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Pricing and Cost Advice
Information Not Available
  • "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."

    • More Spark SQL Pricing and Cost Advice →

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    What do you like most about Spark SQL?
    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.
    Read all 14 answers   →
    What is your experience regarding pricing and costs for Spark SQL?
    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.
    Read all 8 answers   →
    What needs improvement with Spark SQL?
    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 »
    Read all 14 answers   →
    Ranking
    21st
    out of 22 in Hadoop
    Views
    25
    Comparisons
    9
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    4th
    out of 22 in Hadoop
    Views
    1,534
    Comparisons
    1,005
    Reviews
    7
    Average Words per Review
    543
    Rating
    8.3
    Comparisons
    Learn More
    SAP
    Apache
    Overview

    Liberate your data, by making it possible for any data analyst in your company to access and rapidly analyze data in the Hadoop data lake, without burdening your IT team. The Altiscale Insight Cloud handles both real-time and batch analytics, and connects easily to your favorite BI solutions.

    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
    Glu Mobile, Airpush, Devicescape, Visible Measures
    UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, Hitachi Solutions
    Top Industries
    No Data Available
    VISITORS READING REVIEWS
    Financial Services Firm21%
    Computer Software Company14%
    University8%
    Manufacturing Company5%
    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
    April 2024
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    Altiscale is ranked 21st in Hadoop while Spark SQL is ranked 4th in Hadoop with 14 reviews. Altiscale is rated 0.0, while Spark SQL is rated 7.8. On the other hand, the top reviewer of Spark SQL writes "Offers the flexibility to handle large-scale data processing". Altiscale is most compared with , whereas Spark SQL is most compared with Apache Spark, IBM Db2 Big SQL, HPE Ezmeral Data Fabric, SAP HANA and Netezza Analytics.

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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.