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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Apache Spark Streaming

    Score8.7 out of 10
    N/AApache Spark Streaming is a scalable fault-tolerant streaming processing system that natively supports both batch and streaming workloads.N/A

    IBM StreamSets

    Score7.9 out of 10
    N/AIBM® StreamSets enables users to create and manage smart streaming data pipelines through a graphical interface, facilitating data integration across hybrid and multicloud environments. IBM StreamSets can support millions of data pipelines for analytics, applications and hybrid integration.N/A
    Pricing
    Apache Spark StreamingIBM StreamSets
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Apache Spark StreamingIBM StreamSets
    Free Trial
    NoNo
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Apache Spark StreamingIBM StreamSets
    Considered Both Products
    Apache
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    9 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    9 Answers
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    9 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    5 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    8 Answers
    Features
    Apache Spark StreamingIBM StreamSets
    Streaming Analytics
    Comparison of Streaming Analytics features of Apache Spark Streaming and IBM StreamSets
    Feature
    Apache Spark Streaming
    8.4
    1 Ratings
    7% above category average
    IBM StreamSets
    -
    Ratings
    Real-Time Data Analysis8.01 Ratings00 Ratings
    Visualization Dashboards9.01 Ratings00 Ratings
    Data Ingestion from Multiple Data Sources9.01 Ratings00 Ratings
    Low Latency8.01 Ratings00 Ratings
    Integrated Development Tools8.01 Ratings00 Ratings
    Data wrangling and preparation8.01 Ratings00 Ratings
    Linear Scale-Out8.01 Ratings00 Ratings
    Machine Learning Automation9.01 Ratings00 Ratings
    Data Enrichment9.01 Ratings00 Ratings
    Best Alternatives
    Apache Spark StreamingIBM StreamSets
    Small Businesses
    Amazon Kinesis
    Score9.9 out of 10
    No answers on this topic
    Medium-sized Companies
    No answers on this topic
    Apache Spark
    Score8.8 out of 10
    Enterprises
    Spotfire Streaming
    Score5 out of 10
    Apache Spark
    Score8.8 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Apache Spark StreamingIBM StreamSets
    Likelihood to Recommend
    9.0
    (1 ratings)
    7.3
    (9 ratings)
    Usability
    -
    (0 ratings)
    7.7
    (8 ratings)
    User Testimonials
    Apache Spark StreamingIBM StreamSets
    Likelihood to Recommend
    Apache
    Apache Spark Streaming is a tool that we are using for almost a year and is excellent in managing batch processing. It is user-friendly. Using it, we can even process our massive data in fractions of seconds. Its pricing is its other plus point. Only its In-memory processing is its demerit as it occupies a large memory.
    Incentivized
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    IBM
    IBM StreamSets excels in real-time logistics data ingestion and transformation across hybrid systems. It’s less ideal for lightweight ETL tasks or static datasets where simpler tools can achieve similar results with less overhead and complexity.
    Incentivized
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    Pros
    Apache
    • It is amazing in solving complicated transformative logic.
    • It is straightforward to program.
    • It is a very quick tool.
    • It processes large data within a fraction of seconds.
    Incentivized
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    IBM
    • It helps streaming huge data that we have in our Teradata database to various reporting applications that runs on cloud seamlessly.
    • We also use IBM StreamSets to power few BI dashboards that our product managers use on regular basis to showcase various data with clients.
    • I think the data quality is way better compared to Informatica tool.
    Incentivized
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    Cons
    Apache
    • There must be more documentation.
    • It is a profoundly complex tool.
    • Its in-memory processing consumes massive memory.
    Incentivized
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    IBM
    • The error messages I feel aren t always very descriptive so troubleshooting can take longer
    • Maybe more customisation options for scheduling can be done, rest it works pretty well.
    Incentivized
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    Usability
    Apache
    No answers on this topic
    IBM
    The StreamSets platform is very easy to use and the interface is extremely intuitive. The drag-and-drop, low-code design makes it accessible for teams with varying technical skills, allowing us to quickly connect sources, define transformations, and deploy pipelines without heavy coding. StreamSets allows us to get started quickly and not have to worry about our pipelines breaking once they're built.
    Incentivized
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    Alternatives Considered
    Apache
    Apache Spark Streaming stands above all the huge data transformative tools because of its speed of processing which was quite slow in Presto as it takes a lot of our time in the data processing. Spark, comfortably provides integration with Jupyter like notebook environment. and Spark's combination with Jupyter and Python results in enhancing the speed .
    Incentivized
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    IBM
    First advantage is that this software is particularly new and it keeps updating according to the needs of the user. Other advantage is the it organises and produces conclusions on the basis of data without leaving any relevant information. Other softwares lack in data summarising and readability of the charts and sheets they produce.
    Incentivized
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    Return on Investment
    Apache
    • Cost and time-effective tool for our business.
    • We can integrate with Jupyter with many conveniences.
    • Its high-speed data processing has proved beneficial for us.
    Incentivized
    Read full review
    IBM
    • time saving for automatic collection and integration of data
    • time saving thanks to live monitoring and reaction
    • time saving for standardization of data
    Incentivized
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