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Altiscale vs Apache Spark comparison

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Altiscale

25 views|9 comparisons
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Apache Spark

Read 60 Apache Spark reviews
2,498 views|1,884 comparisons
89% willing to recommend
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Buyer's Guide
Hadoop
April 2024
Executive Summary

We performed a comparison between Altiscale and Apache Spark 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
Use Altiscale?
Salvatore Campana
Reduces startup time and gives excellent ROI
Apache Spark helped us with horizontal scalability and cost optimizations.
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pricing and Cost Advice
Information Not Available
  • "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."

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    Questions from the Community
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    What do you like most about Apache Spark?
    Top Answer:We use Spark to process data from different data sources.
    Read all 30 answers   →
    What is your experience regarding pricing and costs for Apache Spark?
    Top Answer:The solution is moderately priced.
    Read all 19 answers   →
    What needs improvement with Apache Spark?
    Top Answer:In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond, and do the transformation in a subsecond
    Read all 32 answers   →
    Ranking
    21st
    out of 22 in Hadoop
    Views
    25
    Comparisons
    9
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    1st
    out of 22 in Hadoop
    Views
    2,498
    Comparisons
    1,884
    Reviews
    25
    Average Words per Review
    432
    Rating
    8.7
    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 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

    Sample Customers
    Glu Mobile, Airpush, Devicescape, Visible Measures
    NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
    Top Industries
    No Data Available
    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%
    Company Size
    No Data Available
    REVIEWERS
    Small Business40%
    Midsize Enterprise19%
    Large Enterprise40%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise12%
    Large Enterprise71%
    Buyer's Guide
    Hadoop
    April 2024
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    Altiscale is ranked 21st in Hadoop while Apache Spark is ranked 1st in Hadoop with 60 reviews. Altiscale is rated 0.0, while Apache Spark is rated 8.4. On the other hand, the top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". Altiscale is most compared with , whereas Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop.

    See our list of best Hadoop vendors.

    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.