Compare Apache Spark vs. IBM Streams

Apache Spark is ranked 1st in Hadoop with 11 reviews while IBM Streams is ranked 6th in Streaming Analytics. Apache Spark is rated 8.0, while IBM Streams is rated 0. The top reviewer of Apache Spark writes "Good Streaming features enable to enter data and analysis within Spark Stream". On the other hand, Apache Spark is most compared with Spring Boot, Azure Stream Analytics and AWS Lambda, whereas IBM Streams is most compared with Apache NiFi, Apache Spark and Confluent.
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Apache Spark Logo
10,923 views|9,163 comparisons
IBM Streams Logo
2,413 views|1,841 comparisons
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Ranking
1st
out of 24 in Hadoop
Views
10,923
Comparisons
9,163
Reviews
10
Average Words per Review
309
Avg. Rating
8.0
6th
out of 27 in Streaming Analytics
Views
2,413
Comparisons
1,841
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Top Comparisons
Compared 35% of the time.
Compared 10% of the time.
Compared 25% of the time.
Compared 20% of the time.
Compared 11% of the time.
Also Known As
IBM InfoSphere Streams
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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.
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Sample Customers
NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi SolutionsGlobo 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
Financial Services Firm29%
Software R&D Company29%
Healthcare Company14%
Non Profit14%
VISITORS READING REVIEWS
Software R&D Company32%
Comms Service Provider12%
Media Company10%
Financial Services Firm9%
VISITORS READING REVIEWS
Software R&D Company32%
Insurance Company16%
Government16%
Comms Service Provider8%
Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: February 2020.
398,890 professionals have used our research since 2012.
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