Apache Spark Streaming vs Talend Data Streams comparison

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Executive Summary

We performed a comparison between Apache Spark Streaming and Talend Data Streams based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Amazon, Confluent and others in Streaming Analytics.
To learn more, read our detailed Streaming Analytics Report (Updated: March 2024).
765,386 professionals have used our research since 2012.
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Pricing and Cost Advice
  • "People pay for Apache Spark Streaming as a service."
  • "I was using the open-source community version, which was self-hosted."
  • "On a scale from one to ten, where one is expensive, or not cost-effective, and ten is cheap, I rate the price a seven."
  • More Apache Spark Streaming Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows.
    Top Answer:In terms of improvement, the UI could be better. Additionally, Spark Streaming works well for various use cases, but improvements could be made for ultra-fast scenarios where seconds matter. While… more »
    Top Answer:As a data engineer, I use Apache Spark Streaming to process real-time data for web page analytics and integrate diverse data sources into centralized data warehouses.
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    Ranking
    8th
    out of 38 in Streaming Analytics
    Views
    4,523
    Comparisons
    3,689
    Reviews
    6
    Average Words per Review
    473
    Rating
    8.2
    22nd
    out of 38 in Streaming Analytics
    Views
    453
    Comparisons
    423
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Comparisons
    Also Known As
    Spark Streaming
    Learn More
    Overview

    Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.

    Talend Data Streams makes streaming data ingestion and integration easier, faster, and more accessible. Plus, Talend Data Streams is built to run completely in the cloud, so no installation is required.
    Sample Customers
    UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.
    Information Not Available
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company19%
    Comms Service Provider7%
    Manufacturing Company6%
    VISITORS READING REVIEWS
    Computer Software Company15%
    Financial Services Firm12%
    Insurance Company11%
    Manufacturing Company11%
    Company Size
    REVIEWERS
    Small Business56%
    Midsize Enterprise11%
    Large Enterprise33%
    VISITORS READING REVIEWS
    Small Business22%
    Midsize Enterprise11%
    Large Enterprise67%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise12%
    Large Enterprise73%
    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.
    765,386 professionals have used our research since 2012.

    Apache Spark Streaming is ranked 8th in Streaming Analytics with 8 reviews while Talend Data Streams is ranked 22nd in Streaming Analytics. Apache Spark Streaming is rated 8.0, while Talend Data Streams is rated 0.0. The top reviewer of Apache Spark Streaming writes "Easy integration, beneficial auto-scaling, and good open-sourced support community". On the other hand, Apache Spark Streaming is most compared with Amazon Kinesis, Azure Stream Analytics, Spring Cloud Data Flow, Confluent and Apache Pulsar, whereas Talend Data Streams is most compared with Databricks, Google Cloud Dataflow, Apache Flink, Starburst Galaxy and Cloudera DataFlow.

    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.