Compare Apache Spark vs. IBM Streams

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Apache Spark Logo
10,877 views|8,741 comparisons
IBM Streams Logo
2,286 views|2,032 comparisons
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Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: July 2021.
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Pricing and Cost Advice
"Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera."

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Questions from the Community
Top Answer: I like that it can handle multiple tasks parallelly. I also like the automation feature. JavaScript also helps with the parallel streaming of the library.
Top Answer: Apache Spark is open-source. You have to pay only when you use any bundled product, such as Cloudera.
Top Answer: The logging for the observability platform could be better.
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Ranking
1st
out of 22 in Hadoop
Views
10,877
Comparisons
8,741
Reviews
12
Average Words per Review
441
Rating
8.6
12th
out of 35 in Streaming Analytics
Views
2,286
Comparisons
2,032
Reviews
0
Average Words per Review
0
Rating
N/A
Popular Comparisons
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 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
Financial Services Firm40%
Computer Software Company20%
Marketing Services Firm10%
Non Profit10%
VISITORS READING REVIEWS
Computer Software Company23%
Comms Service Provider19%
Financial Services Firm11%
Media Company9%
VISITORS READING REVIEWS
Computer Software Company29%
Comms Service Provider14%
Financial Services Firm13%
Retailer6%
Company Size
REVIEWERS
Small Business36%
Midsize Enterprise21%
Large Enterprise42%
No Data Available
Find out what your peers are saying about Apache, Cloudera, IBM and others in Hadoop. Updated: July 2021.
521,189 professionals have used our research since 2012.

Apache Spark is ranked 1st in Hadoop with 10 reviews while IBM Streams is ranked 12th in Streaming Analytics. Apache Spark is rated 8.6, while IBM Streams is rated 0.0. 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, AWS Batch, SAP HANA and HPE Ezmeral Data Fabric, whereas IBM Streams is most compared with Confluent, Apache NiFi, Google Cloud Dataflow, Azure Stream Analytics and Amazon Kinesis.

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