Cloudera DataFlow vs IBM Streams comparison

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Cloudera Logo
1,908 views|977 comparisons
66% willing to recommend
IBM Logo
644 views|569 comparisons
100% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Cloudera DataFlow and IBM Streams based on real PeerSpot user reviews.

Find out what your peers are saying about Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics.
To learn more, read our detailed Streaming Analytics Report (Updated: April 2024).
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Featured Review
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
  • "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: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.
    Top Answer:The solution’s licenses pricing is different from one region to another region. I rate the solution’s pricing a seven out of ten.
    Top Answer:the limited number of connectors. This shall be overcome with work-arounds or eventually buying additional connectors to complete the solution.
    Top Answer:We use the solution for data pipeline by modernizing the traditional ETL jobs done through advanced streaming. Another use case is building the g2g streaming platform, which facilitates data exchange… more »
    Ranking
    13th
    out of 38 in Streaming Analytics
    Views
    1,908
    Comparisons
    977
    Reviews
    3
    Average Words per Review
    288
    Rating
    6.7
    15th
    out of 38 in Streaming Analytics
    Views
    644
    Comparisons
    569
    Reviews
    1
    Average Words per Review
    447
    Rating
    7.0
    Comparisons
    Also Known As
    CDF, Hortonworks DataFlow, HDF
    IBM InfoSphere Streams
    Learn More
    Overview

    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.

    IBM Streams is an advanced analytic platform that allows user-developed applications to quickly ingest, analyze and correlate information as it arrives from thousands of data stream sources. The solution can handle very high data throughput rates, up to millions of events or messages per second. Streams helps you analyze data in motion, simplify development of streaming applications, and extend the value of existing systems.
    Sample Customers
    Clearsense
    Globo TV, All England Lawn Tennis Club, CenterPoint Energy, Consolidated Communications Holdings, Darwin Ecosystem, Emory University Hospital, ICICI Securities, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Living Roads, Mobileum, Optibus, Southern Ontario Smart Computing Innovation Platform (SOSCIP), University of Alberta, University of Montana, University of Ontario Institute of Technology, Wimbledon 2015
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company19%
    Financial Services Firm15%
    University8%
    Government7%
    VISITORS READING REVIEWS
    Financial Services Firm23%
    Computer Software Company15%
    Comms Service Provider6%
    Healthcare Company5%
    Company Size
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise10%
    Large Enterprise74%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise10%
    Large Enterprise73%
    Buyer's Guide
    Streaming Analytics
    April 2024
    Find out what your peers are saying about Amazon Web Services (AWS), Databricks, Microsoft and others in Streaming Analytics. Updated: April 2024.
    770,141 professionals have used our research since 2012.

    Cloudera DataFlow is ranked 13th in Streaming Analytics with 3 reviews while IBM Streams is ranked 15th in Streaming Analytics with 5 reviews. Cloudera DataFlow is rated 6.6, while IBM Streams is rated 8.2. The top reviewer of Cloudera DataFlow writes "A scalable and robust platform for analyzing data". On the other hand, the top reviewer of IBM Streams writes "A solution for data pipelines but has connector limitations". Cloudera DataFlow is most compared with Databricks, Confluent, Amazon MSK, Informatica Data Engineering Streaming and Hortonworks Data Platform, whereas IBM Streams is most compared with Confluent, Apache Spark, Azure Stream Analytics, Apache Flink and Amazon MSK.

    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.