Amazon MSK vs Cloudera DataFlow comparison

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8,163 views|6,453 comparisons
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1,988 views|1,068 comparisons
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Amazon MSK and Cloudera DataFlow based on real PeerSpot user reviews.

Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Amazon MSK vs. Cloudera DataFlow Report (Updated: March 2024).
765,234 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"It is a stable product.""Overall, it is very cost-effective based on the workflow.""The most valuable feature of Amazon MSK is the integration.""Amazon MSK has significantly improved our organization by building seamless integration between systems.""It offers good stability.""MSK has a private network that's an out-of-box feature."

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"The initial setup was not so difficult""DataFlow's performance is okay.""This solution is very scalable and robust."

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Cons
"The product's schema support needs enhancement. It will help enhance integration with many kinds of languages of programming languages, especially for environments using languages like .NET.""The configuration seems a little complex and the documentation on the product is not available.""It would be really helpful if Amazon MSK could provide a single installation that covers all the servers.""Amazon MSK could improve on the features they offer. They are still lagging behind Confluence.""It does not autoscale. Because if you do keep it manually when you add a note to the cluster and then you register it, then it is scalable, but the fact that you have to go and do it, I think, makes it, again, a bit of some operational overhead when managing the cluster.""It should be more flexible, integration-wise."

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"It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists.""Although their workflow is pretty neat, it still requires a lot of transformation coding; especially when it comes to Python and other demanding programming languages.""It is not easy to use the R language. Though I don't know if it's possible, I believe it is possible, but it is not the best language for machine learning."

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Pricing and Cost Advice
  • "The price of Amazon MSK is less than some competitor solutions, such as Confluence."
  • "The platform has better pricing than one of its competitors."
  • More Amazon MSK Pricing and Cost Advice →

  • "DataFlow isn't expensive, but its value for money isn't great."
  • More Cloudera DataFlow Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Amazon MSK has significantly improved our organization by building seamless integration between systems.
    Top Answer:The product's schema support needs enhancement. It will help enhance integration with many kinds of languages of programming languages, especially for environments using languages like .NET. They… more »
    Top Answer:We use the software to facilitate building integrations between systems.
    Top Answer:The initial setup was not so difficult
    Top Answer:It is not easy to use the R language. Though I don't know if it's possible, I believe it is possible, but it is not the best language for machine learning. This feature could be improved.
    Top Answer:Sometimes I need this workflow to make my modules, not for campaign preparation. It is solely focused on developing quality modules for direct telecommunication companies.
    Ranking
    6th
    out of 38 in Streaming Analytics
    Views
    8,163
    Comparisons
    6,453
    Reviews
    5
    Average Words per Review
    427
    Rating
    7.0
    13th
    out of 38 in Streaming Analytics
    Views
    1,988
    Comparisons
    1,068
    Reviews
    3
    Average Words per Review
    288
    Rating
    6.7
    Comparisons
    Also Known As
    Amazon Managed Streaming for Apache Kafka
    CDF, Hortonworks DataFlow, HDF
    Learn More
    Overview

    Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that enables you to build and run applications that use Apache Kafka to process streaming data. Amazon MSK provides the control-plane operations, such as those for creating, updating, and deleting clusters.

    Cloudera DataFlow (CDF) is a comprehensive edge-to-cloud real-time streaming data platform that gathers, curates, and analyzes data to provide customers with useful insight for immediately actionable intelligence. It resolves issues with real-time stream processing, streaming analytics, data provenance, and data ingestion from IoT devices and other sources that are associated with data in motion. Cloudera DataFlow enables secure and controlled data intake, data transformation, and content routing because it is built entirely on open-source technologies. With regard to all of your strategic digital projects, Cloudera DataFlow enables you to provide a superior customer experience, increase operational effectiveness, and maintain a competitive edge.

    With Cloudera DataFlow, you can take the next step in modernizing your data streams by connecting your on-premises flow management, streams messaging, and stream processing and analytics capabilities to the public cloud.

    Cloudera DataFlow Advantage Features

    Cloudera DataFlow has many valuable key features. Some of the most useful ones include:

    • Edge and flow management: Edge agents and an edge management hub work together to provide the edge management capability. Edge agents can be managed, controlled, and watched over in order to gather information from edge hardware and push intelligence back to the edge. Thousands of edge devices can now be used to design, deploy, run, and monitor edge flow apps. Edge Flow Manager (EFM) is an agent management hub that enables the development, deployment, and monitoring of edge flows on thousands of MiNiFi agents using a graphical flow-based programming model.
    • Streams messaging: The CDF platform guarantees that all ingested data streams can be temporarily buffered so that other applications can use the data as needed. This makes it possible for a business to scale efficiently, as data streams from thousands of origination points start to grow to petabyte sizes. To achieve IoT-scale, streams messaging allows you to buffer large data streams using a publish-subscribe strategy.
    • Stream analytics and processing: The third tenet of the CDF platform is its capacity to analyze incoming data streams in real time and with minimal latency, providing actionable intelligence in the form of predictive and prescriptive insights. This stage is essential to completing the Data-in-Motion lifecycle for an enterprise because there is only a use in absorbing all real-time streams if something useful is done with them in the moment to benefit your company.
    • Shared Data Experience (SDX): The most crucial component that transforms CDF into a genuine platform is Cloudera Data Platform's SDX. It is a powerful data fabric that offers the broadest possible deployment flexibility and guarantees total security, governance, and control across infrastructures. You get a single experience for security (with Apache Ranger), governance (with Apache Atlas), and data lineage from edge to cloud because all the CDF components seamlessly connect with SDX.

    Cloudera DataFlow Advantage Benefits

    There are many benefits to implementing Cloudera DataFlow . Some of the biggest advantages the solution offers include:

    • Completely open source: Invest in your architecture with confidence, knowing that there will be no vendor lock-in.
    • More than 300 pre-built processors: This is the only product that provides edge-to-cloud connection this comprehensive as well as a no-code user experience
    • Integrated data provenance: The market's only platform that offers out-of-the-box, end-to-end data lineage tracking and provenance across MiNiFi, NiFi, Kafka, Flink, and more.
    • Multiple stream processing engines to choose from: Supports Spark structured streaming, Kafka Streams, and Apache Flink for real-time insights and predictive analytics.
    • Hundred of Kafka consumers: Cloudera has hundreds of satisfied customers who receive exceptional support for their complex Kafka implementations.
    • Use cases for edge IoT: IoT data from thousands of endpoints may be easily collected, processed, and managed from the edge to the cloud with a multi-cloud/hybrid cloud strategy.
    • Hybrid/multi-cloud approach: Choose a flexible deployment option for your streaming architecture that spans across edge, on-premises, and various cloud environments with ease thanks to the power of CDP.

    Sample Customers
    Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
    Clearsense
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company18%
    Manufacturing Company8%
    Retailer5%
    VISITORS READING REVIEWS
    Computer Software Company18%
    Financial Services Firm14%
    University8%
    Educational Organization7%
    Company Size
    VISITORS READING REVIEWS
    Small Business19%
    Midsize Enterprise12%
    Large Enterprise69%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise11%
    Large Enterprise74%
    Buyer's Guide
    Amazon MSK vs. Cloudera DataFlow
    March 2024
    Find out what your peers are saying about Amazon MSK vs. Cloudera DataFlow and other solutions. Updated: March 2024.
    765,234 professionals have used our research since 2012.

    Amazon MSK is ranked 6th in Streaming Analytics with 6 reviews while Cloudera DataFlow is ranked 13th in Streaming Analytics with 3 reviews. Amazon MSK is rated 7.2, while Cloudera DataFlow is rated 6.6. The top reviewer of Amazon MSK writes "Efficient real-time transaction tracking but time-consuming installation". On the other hand, the top reviewer of Cloudera DataFlow writes "A scalable and robust platform for analyzing data". Amazon MSK is most compared with Confluent, Amazon Kinesis, Azure Stream Analytics, Google Cloud Dataflow and Instaclustr Managed Apache Kafka, whereas Cloudera DataFlow is most compared with Databricks, Confluent, Spring Cloud Data Flow, Hortonworks Data Platform and Informatica Data Engineering Streaming. See our Amazon MSK vs. Cloudera DataFlow report.

    See our list of best Streaming Analytics vendors.

    We monitor all Streaming Analytics 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.