Fujitsu Interstage Big Data Complex Event Processing Server [EOL] vs Spring Cloud Data Flow comparison

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We performed a comparison between Fujitsu Interstage Big Data Complex Event Processing Server [EOL] and Spring Cloud Data Flow based on real PeerSpot user reviews.

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  • "This is an open-source product that can be used free of charge."
  • "If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."
  • More Spring Cloud Data Flow Pricing and Cost Advice →

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    Top Answer:Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD… more »
    Top Answer:Spring Cloud Data Flow is used for asynchronous workloads. We are working on streams. For example, a workload is generated at a particular point, and at the source, it gets passed down through a… more »
    Top Answer:The solution requires little maintenance. My advice to others is for them to follow the documentation. The solution is very well-designed and they deliver on their promises. I rate Spring Cloud Data… more »
    Ranking
    Unranked
    In Streaming Analytics
    10th
    out of 38 in Streaming Analytics
    Views
    3,998
    Comparisons
    3,018
    Reviews
    1
    Average Words per Review
    610
    Rating
    7.0
    Comparisons
    Also Known As
    Interstage Big Data Complex Event Processing Server
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    Overview

    Interstage Big Data Complex Event Processing Server is a complex event processing software platform that uses Fujitsu's proprietary high-speed filter technology to automatically scope large volumes of events and compare them with the system's master data files, thereby making it possible to quickly identify important events. Scoping rules for the high-speed filter can be defined using brief, easy-to-understand descriptions that include names and terminology used in normal operations.

    Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
    Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.

    Top Industries
    No Data Available
    VISITORS READING REVIEWS
    Financial Services Firm29%
    Computer Software Company16%
    Manufacturing Company7%
    Retailer7%
    Company Size
    No Data Available
    VISITORS READING REVIEWS
    Small Business13%
    Midsize Enterprise9%
    Large Enterprise77%
    Buyer's Guide
    Streaming Analytics
    March 2024
    Find out what your peers are saying about Databricks, Amazon, Confluent and others in Streaming Analytics. Updated: March 2024.
    765,234 professionals have used our research since 2012.

    Fujitsu Interstage Big Data Complex Event Processing Server [EOL] doesn't meet the minimum requirements to be ranked in Streaming Analytics while Spring Cloud Data Flow is ranked 10th in Streaming Analytics with 5 reviews. Fujitsu Interstage Big Data Complex Event Processing Server [EOL] is rated 0.0, while Spring Cloud Data Flow is rated 8.0. On the other hand, the top reviewer of Spring Cloud Data Flow writes "Good logging mechanisms, a strong infrastructure and pretty scalable". Fujitsu Interstage Big Data Complex Event Processing Server [EOL] is most compared with , whereas Spring Cloud Data Flow is most compared with Apache Flink, Google Cloud Dataflow, Apache Spark Streaming, Azure Data Factory and Mule Anypoint Platform.

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    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.