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Apache Spark vs IBM Streams comparison

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Apache Spark

Read 60 Apache Spark reviews
2,498 views|1,884 comparisons
89% willing to recommend
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IBM Streams

Read 5 IBM Streams reviews
674 views|593 comparisons
100% willing to recommend
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Buyer's Guide
Hadoop
April 2024
Executive Summary

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

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.
To learn more, read our detailed Hadoop Report (Updated: April 2024).
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Featured Review
Anonymous User
Seamless in distributing tasks, including its impressive map-reduce functionality
I have an example. We had a single-threaded application that used to run for about four to five hours, but with Spark, it got reduced to under one... Read more →
Anonymous User
Researched Apache Spark but chose IBM Streams: The product has enabled us to create solutions to client problems that would have either been impossible or very expensive/difficult using other technologies.
The product has enabled us to create solutions to client problems that would have either been impossible or very expensive/difficult using other... Read more →
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
  • "Since we are using the Apache Spark version, not the data bricks version, it is an Apache license version, the support and resolution of the bug are actually late or delayed. The Apache license is free."
  • "Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."
  • "We are using the free version of the solution."
  • "Apache Spark is not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."
  • "Apache Spark is an expensive solution."
  • "Spark is an open-source solution, so there are no licensing costs."
  • "On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
  • "It is an open-source solution, it is free of charge."

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    Questions from the Community
    What do you like most about Apache Spark?
    Top Answer:We use Spark to process data from different data sources.
    Read all 30 answers   →
    What is your experience regarding pricing and costs for Apache Spark?
    Top Answer:The solution is moderately priced.
    Read all 19 answers   →
    What needs improvement with Apache Spark?
    Top Answer:In data analysis, you need to take real-time data from different data sources. You need to process this in a subsecond, and do the transformation in a subsecond
    Read all 32 answers   →
    What is your experience regarding pricing and costs for IBM Streams?
    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.
    What needs improvement with IBM Streams?
    Top Answer:the limited number of connectors. This shall be overcome with work-arounds or eventually buying additional connectors to complete the solution.
    What is your primary use case for IBM Streams?
    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
    1st
    out of 22 in Hadoop
    Views
    2,498
    Comparisons
    1,884
    Reviews
    25
    Average Words per Review
    432
    Rating
    8.7
    15th
    out of 38 in Streaming Analytics
    Views
    674
    Comparisons
    593
    Reviews
    1
    Average Words per Review
    447
    Rating
    7.0
    Comparisons
    Spring Boot logo
    Spring Boot vs. Apache Spark
    Compared 31% of the time.
    AWS Batch logo
    AWS Batch vs. Apache Spark
    Compared 10% of the time.
    Spark SQL logo
    Spark SQL vs. Apache Spark
    Compared 10% of the time.
    SAP HANA logo
    SAP HANA vs. Apache Spark
    Compared 8% of the time.
    More Apache Spark Competitors   →
    Confluent logo
    Confluent vs. IBM Streams
    Compared 44% of the time.
    Apache Flink logo
    Apache Flink vs. IBM Streams
    Compared 11% of the time.
    Apache NiFi logo
    Apache NiFi vs. IBM Streams
    Compared 8% of the time.
    Amazon MSK logo
    Amazon MSK vs. IBM Streams
    Compared 8% of the time.
    More IBM Streams Competitors   →
    Also Known As
    IBM InfoSphere Streams
    Learn More
    Apache
    IBM
    Overview

    Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory

    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
    NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
    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
    REVIEWERS
    Computer Software Company30%
    Financial Services Firm15%
    University9%
    Marketing Services Firm6%
    VISITORS READING REVIEWS
    Financial Services Firm24%
    Computer Software Company13%
    Manufacturing Company7%
    Comms Service Provider6%
    VISITORS READING REVIEWS
    Financial Services Firm23%
    Computer Software Company15%
    Comms Service Provider6%
    Real Estate/Law Firm5%
    Company Size
    REVIEWERS
    Small Business40%
    Midsize Enterprise19%
    Large Enterprise40%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise12%
    Large Enterprise71%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise10%
    Large Enterprise72%
    Buyer's Guide
    Hadoop
    April 2024
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    Apache Spark is ranked 1st in Hadoop with 60 reviews while IBM Streams is ranked 15th in Streaming Analytics with 5 reviews. Apache Spark is rated 8.4, while IBM Streams is rated 8.2. The top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". On the other hand, the top reviewer of IBM Streams writes "A solution for data pipelines but has connector limitations". Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop, whereas IBM Streams is most compared with Confluent, Azure Stream Analytics, Apache Flink, Apache NiFi and Amazon MSK.

    We monitor all Hadoop 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.