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Amazon Kinesis vs IBM Streams comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
7.8
Amazon Kinesis offers significant savings, enhances data processing and integration, and improves security and auditing, essential for architecture development.
No sentiment score available
 

Customer Service

No sentiment score available
Sentiment score
7.8
IBM Streams customer support is praised for excellent tech support, proactive service, and a strong professional forum.
 

Scalability Issues

No sentiment score available
Sentiment score
9.0
IBM Streams is scalable and efficient for large data, supporting government and finance needs with low latency and efficient clustering.
 

Stability Issues

No sentiment score available
Sentiment score
5.8
IBM Streams is stable, enterprise-class software with reliable operators, though IDE crashes and external interface issues can occur.
 

Room For Improvement

IBM Streams needs enhancements in debugging, Python support, machine learning tools, dynamic scaling, and connector availability to reduce custom solutions.
 

Setup Cost

Amazon Kinesis pricing is fair and cost-effective for some, though costs rise with data volume and usage.
 

Valuable Features

IBM Streams offers scalable, real-time analytics with Java, diverse connectors, and toolkits, benefiting healthcare and time series data processing.
 

Categories and Ranking

Amazon Kinesis
Ranking in Streaming Analytics
2nd
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
27
Ranking in other categories
No ranking in other categories
IBM Streams
Ranking in Streaming Analytics
18th
Average Rating
8.2
Reviews Sentiment
7.2
Number of Reviews
5
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of December 2024, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 10.1%, down from 15.4% compared to the previous year. The mindshare of IBM Streams is 0.8%, down from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Rajni Kumar Jha - PeerSpot reviewer
Used for media streaming and live-streaming data
It is not compulsory to use Amazon Kinesis. If you don't want to use the data streaming, you can use just the Kinesis data firehose. Using the Kinesis data firehose is compulsory because we can't store all chats and recordings in Amazon S3 without it. When a call comes in the Amazon Kinesis instance, it will go to Data Streams if we use it. Otherwise, it will go to the Kinesis data firehose, where we need to define the S3 bucket path, and it will go to Amazon S3. So, without the Kinesis data firehose, we can't store all the chats and recordings in Amazon S3. Using Amazon Kinesis totally depends upon the user's requirements. If you want to use live streaming for the data lake or data analyst team, you need to use Amazon Kinesis. If you don't want to use it, you can directly use the Kinesis data firehose, which will be stored in Amazon S3. Overall, I rate the solution an eight out of ten.
Ahmed_Emad - PeerSpot reviewer
A solution for data pipelines but has connector limitations
We have used Kafka for seven years. IBM streams gives you many OOTB features that can boost the time-to-market, especially when it comes to reporting and monitoring for example. Confluent is recognized as one of the leaders in this space and the main reason for this is related to the complete vision of the platform also the large number of connectors. This gives the edge and competitive advatnage.
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Top Industries

By visitors reading reviews
Computer Software Company
18%
Financial Services Firm
18%
Manufacturing Company
10%
Retailer
5%
Financial Services Firm
32%
Computer Software Company
20%
Healthcare Company
5%
Retailer
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Amazon Kinesis?
Amazon Kinesis's main purpose is to provide near real-time data streaming at a consistent 2Mbps rate, which is really impressive.
What is your experience regarding pricing and costs for Amazon Kinesis?
Amazon Kinesis is moderately priced. In comparison with other competitors, it is fairly priced, however, if they reduced the price a little, it could add more value to customers.
What needs improvement with Amazon Kinesis?
I do not see any scope for improvement as it does what it is supposed to do. No changes are required. Since it's predominantly a back-end service, any end-user isn't going to interact with it direc...
What is your experience regarding pricing and costs for IBM Streams?
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?
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?
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 exchan...
 

Comparisons

 

Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis
IBM InfoSphere Streams
 

Overview

 

Sample Customers

Zillow, Netflix, Sonos
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
Find out what your peers are saying about Amazon Kinesis vs. IBM Streams and other solutions. Updated: December 2024.
824,067 professionals have used our research since 2012.