Apache Spark Streaming vs IBM Streams comparison

Cancel
You must select at least 2 products to compare!
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Apache Spark Streaming and IBM 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).
763,955 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:
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 →

    Information Not Available
    report
    Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.
    763,955 professionals have used our research since 2012.
    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.
    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
    8th
    out of 38 in Streaming Analytics
    Views
    4,523
    Comparisons
    3,689
    Reviews
    6
    Average Words per Review
    473
    Rating
    8.2
    15th
    out of 38 in Streaming Analytics
    Views
    678
    Comparisons
    598
    Reviews
    1
    Average Words per Review
    447
    Rating
    7.0
    Comparisons
    Also Known As
    Spark Streaming
    IBM InfoSphere Streams
    Learn More
    Overview

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

    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
    UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.
    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
    Financial Services Firm19%
    Computer Software Company19%
    Comms Service Provider7%
    Manufacturing Company6%
    VISITORS READING REVIEWS
    Financial Services Firm24%
    Computer Software Company14%
    Comms Service Provider6%
    Government6%
    Company Size
    REVIEWERS
    Small Business56%
    Midsize Enterprise11%
    Large Enterprise33%
    VISITORS READING REVIEWS
    Small Business21%
    Midsize Enterprise12%
    Large Enterprise67%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise9%
    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.
    763,955 professionals have used our research since 2012.

    Apache Spark Streaming is ranked 8th in Streaming Analytics with 6 reviews while IBM Streams is ranked 15th in Streaming Analytics with 1 review. Apache Spark Streaming is rated 8.0, while IBM Streams is rated 8.2. The top reviewer of Apache Spark Streaming writes "Easy deployment as a cluster and good documentation". On the other hand, the top reviewer of IBM Streams writes "A solution for data pipelines but has connector limitations". Apache Spark Streaming is most compared with Amazon Kinesis, Azure Stream Analytics, Spring Cloud Data Flow, Confluent and Apache Pulsar, whereas IBM Streams is most compared with Confluent, Azure Stream Analytics, Apache Spark, Apache Flink and Google Cloud 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.