Apache Storm vs Google Cloud Dataflow comparison

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Executive Summary

We performed a comparison between Apache Storm and Google Cloud Dataflow based on real PeerSpot user reviews.

Find out what your peers are saying about Amazon, Apache, Zadara and others in Compute Service.
To learn more, read our detailed Compute Service Report (Updated: March 2024).
765,386 professionals have used our research since 2012.
Featured Review
Quotes From Members
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Here are some excerpts of what they said:
Pricing and Cost Advice
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  • "The price of the solution depends on many factors, such as how they pay for tools in the company and its size."
  • "Google Cloud is slightly cheaper than AWS."
  • "The tool is cheap."
  • "Google Cloud Dataflow is a cheap solution."
  • "The solution is cost-effective."
  • "On a scale from one to ten, where one is cheap, and ten is expensive, I rate Google Cloud Dataflow's pricing a four out of ten."
  • "On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a seven to eight out of ten."
  • "The solution is not very expensive."
  • More Google Cloud Dataflow Pricing and Cost Advice →

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    Top Answer:The product's installation process is easy...The tool's maintenance part is somewhat easy.
    Top Answer:The authentication part of the product is an area of concern where improvements are required. For some common users, the solution's authentication part is difficult to use. The scalability of the… more »
    Ranking
    13th
    out of 16 in Compute Service
    Views
    385
    Comparisons
    323
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    7th
    out of 38 in Streaming Analytics
    Views
    4,831
    Comparisons
    4,043
    Reviews
    10
    Average Words per Review
    308
    Rating
    7.7
    Comparisons
    Also Known As
    Google Dataflow
    Learn More
    Overview
    Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm is simple and can be used with any programming language.
    Google Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.
    Sample Customers
    Groupon, Spotify, The Weather Channel, Twitter, FullContact
    Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm26%
    Computer Software Company14%
    University9%
    Retailer7%
    VISITORS READING REVIEWS
    Financial Services Firm14%
    Computer Software Company12%
    Retailer11%
    Manufacturing Company10%
    Company Size
    VISITORS READING REVIEWS
    Small Business13%
    Midsize Enterprise8%
    Large Enterprise79%
    REVIEWERS
    Small Business27%
    Midsize Enterprise18%
    Large Enterprise55%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise12%
    Large Enterprise71%
    Buyer's Guide
    Compute Service
    March 2024
    Find out what your peers are saying about Amazon, Apache, Zadara and others in Compute Service. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    Apache Storm is ranked 13th in Compute Service while Google Cloud Dataflow is ranked 7th in Streaming Analytics with 10 reviews. Apache Storm is rated 0.0, while Google Cloud Dataflow is rated 7.8. On the other hand, the top reviewer of Google Cloud Dataflow writes "Easy to use for programmers, user-friendly, and scalable". Apache Storm is most compared with Apache NiFi, Azure Stream Analytics and AWS Lambda, whereas Google Cloud Dataflow is most compared with Databricks, Apache NiFi, Amazon Kinesis, Amazon MSK and Spring Cloud Data Flow.

    We monitor all Compute Service 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.