Amazon Kinesis vs IBM Streams comparison

Why PeerSpot?

Amazon Web Services (AWS) and IBM are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #11 with an average rating of 8.0, while IBM is ranked #23. Amazon Web Services (AWS) holds a 3.8% mindshare in SA, compared to IBM’s 2.1% mindshare. Additionally, 90% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Amazon Kinesis

Read 29 Amazon Kinesis reviews

3,589 Views
3,589 Comparison Views

90% willing to recommend

IBM Streams

Read 5 IBM Streams reviews

1,629 Views
1,303 Comparison Views

100% willing to recommend

Amazon Kinesis

IBM Streams

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

IBM Streams and Amazon Kinesis compete in the real-time data stream processing category. While both have unique strengths, Amazon Kinesis offers an edge in scalability and AWS ecosystem integration.

Features: IBM Streams offers complex event processing, deep integration within IBM's ecosystem, and supports comprehensive real-time analytics, ideal for organizations invested in IBM technology. Amazon Kinesis provides easy scalability, native integration with AWS services, and robust cloud processing capabilities suitable for various data applications.

Room for Improvement: IBM Streams could improve by simplifying its deployment process and lowering its reliance on IBM-specific expertise. Amazon Kinesis may benefit from enhancements in cost management, fine-tuning data processing times, and improving scalability beyond AWS boundaries for more versatile data workload handling.

Ease of Deployment and Customer Service: IBM Streams requires expertise in IBM configurations, adding complexity for new users, though it supports extensive use cases. Amazon Kinesis offers straightforward cloud deployments with the support of AWS's technical network, attracting organizations seeking rapid and scalable implementation.

Pricing and ROI: IBM Streams tends to involve higher initial setup costs due to its specialized infrastructure and IBM ecosystem integration. Over time, its ROI can be substantial for IBM-reliant businesses. In contrast, Amazon Kinesis benefits from a pay-as-you-go pricing model, providing immediate cost savings and scalable ROI for growing cloud-based projects.

To learn more, read our detailed Amazon Kinesis vs. IBM Streams Report (Updated: September 2026).

Buyer's Guide

Amazon Kinesis vs. IBM Streams

September 2026

Download the complete report

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Review summaries and opinions

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

Categories and Ranking

Amazon Kinesis

Ranking in Streaming Analytics

11th

Average Rating

8.0

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

IBM Streams

Ranking in Streaming Analytics

23rd

Average Rating

8.2

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2026, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 3.8%, down from 6.6% compared to the previous year. The mindshare of IBM Streams is 2.1%, up from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Amazon Kinesis	3.8%
IBM Streams	2.1%
Other	94.1%

Streaming Analytics

Featured Reviews

reviewer1480695

Director of Software Development at a tech vendor with 10,001+ employees

Has enabled real-time processing of critical event streams with seamless cloud integration

We are contemplating moving away from Amazon Kinesis primarily because of the cost. It is very useful, but if we write our own analytics and data processing pipeline, it would be much cheaper for us. The cost is a primary hindrance. That's why we are not using it widely. For our critical pipeline we are using it, but after that we are putting it in an S3 bucket. Other pipelines directly put the events in an S3 bucket and then process from there. There is no lack of functions in Amazon Kinesis. Functionality-wise, we feel it's complete. The cost aspect is what we are really concerned about.

Read full review

Ahmed_Emad

Territory Sales Leader at Sumerge

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.

Read full review

Quotes from Members

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

Pros

"Amazon Kinesis's main purpose is to provide near real-time data streaming at a consistent 2Mbps rate, which is really impressive."

"The integration between Amazon Kinesis and Lambda helps us significantly."

"With AWS, you don't have to invest in any kind of infrastructure."

"Setting Amazon Kinesis up is quick and easy; it only takes a few minutes to configure the necessary settings and start using it."

"The integration capabilities of the product are good."

"From my experience, one of the most valuable features is the ability to track silent events on endpoints. Previously, these events might have gone unnoticed, but now we can access them within the product range. For example, if a customer reports that their calls are not reaching the portal files, we can use this feature to troubleshoot and optimize the system."

"The solution has the capacity to store the data anywhere from one day to a week and provides limitless storage for us."

"I find almost all features valuable, especially the timing and fast pace movement."

More Amazon Kinesis pros

"The OEM Solution (Excel-medical.com) running on top of IBM Streams provides real-time clinical algorithms that can give better insight into the patient's acuity, thus cutting off time to discharge patients and inversely making sure that sick patients don't get discharged until ready."

"As a result, the TELCO company was able to cut down the time it took to respond to customer needs and there were fewer complaints."

"The product has enabled us to create solutions to client problems that would have either been impossible or very expensive/difficult using other technologies."

"Easy development and deployment, Java implementation features, and the real time analyser and alarm function are the most valuable features for us."

Cons

"Could include features that make it easier to scale."

"There could be valid data in Kinesis that is not being processed, which affects stability. Although it rarely happens, this issue has been observed in many deployments, making it not completely stable."

"Amazon Kinesis has a less meaningful and easy use than Azure Event Hub."

"Amazon Kinesis could improve its pricing to be more competitive, especially for large volumes."

"Amazon Kinesis should improve its limits."

"AI processing or cleaning up data would be nice since I don't think it is a feature in Amazon Kinesis right now."

"We were charged high costs for the solution’s enhanced fan-out feature."

"For me, especially with video streams, there's sometimes a kind of delay when the data has to be pumped to other services. This delay could be improved in Kinesis, or especially the Kinesis Video Streams, which is being used for different use cases for Amazon Connect. With that improvement, a lot of other use cases of Amazon Connect integrating with third-party analytic tools would be easier."

More Amazon Kinesis cons

"We had some stability issues where we used embedded Zookeeper in production."

"The development IDE sometimes crashes and freezes."

"The price and versatility of this product need to improve - it is not inexpensive."

"I’d like to see a tool kit specifically targeted at incremental machine learning. It’s already great for scoring previously trained models, but dynamically updating models is currently more of a 'grow your own' kind of thing."

Pricing and Cost Advice

"It was actually a fairly high volume we were spending. We were spending about 150 a month."

"Amazon Kinesis is an expensive solution."

"Amazon Kinesis pricing is sometimes reasonable and sometimes could be better, depending on the planning, so it's a five out of ten for me."

"The solution's pricing is fair."

"In general, cloud services are very convenient to use, even if we have to pay a bit more, as we know what we are paying for and can focus on other tasks."

"The tool's entry price is cheap. However, pricing increases with data volume."

"The product falls on a bit of an expensive side."

"Under $1,000 per month."

More Amazon Kinesis pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

Outsourcing Company

University

Government

16%

Financial Services Firm

15%

Construction Company

13%

Comms Service Provider

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	10
Large Enterprise	10

No data available

Questions from the Community

What is your experience regarding pricing and costs for Amazon Kinesis?

Amazon Kinesis and Lambda pricing is competitive, but we noticed that scaling and large volumes could potentially increase costs significantly.

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What needs improvement with Amazon Kinesis?

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What is your primary use case for Amazon Kinesis?

We use Amazon Kinesis for stream processing. We get events from on-premise devices to the cloud. We get many device events and we have to process these events that are coming from the devices. To p...

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Comparisons

Azure Stream Analytics vs Amazon Kinesis

Compared 14% of the time

Confluent vs Amazon Kinesis

Compared 14% of the time

Apache Flink vs Amazon Kinesis

Compared 12% of the time

Amazon MSK vs Amazon Kinesis

Compared 9% of the time

Redpanda vs Amazon Kinesis

Compared 8% of the time

More Amazon Kinesis Competitors

Azure Stream Analytics vs IBM Streams

Compared 23% of the time

Confluent vs IBM Streams

Compared 18% of the time

Apache NiFi vs IBM Streams

Compared 11% of the time

Apache Flink vs IBM Streams

Compared 11% of the time

Apache Spark Streaming vs IBM Streams

Compared 2% of the time

More IBM Streams Competitors

Product Reports

Buyer's Guide

Amazon Kinesis

October 2026

Download Amazon Kinesis product report

Buyer's Guide

Streaming Analytics

October 2026

Download IBM Streams product report

Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis

IBM InfoSphere Streams

Overview

Amazon Kinesis provides real-time data streaming with seamless AWS integration, ideal for analytics, data transformation, and external customer feeds. It offers cost-effective data management with high throughput and low latency, supporting multiple programming languages.

Amazon Kinesis enables organizations to manage real-time data streams efficiently. Its integration with AWS ensures seamless setup and operation, while features like auto-scaling and fault tolerance make it reliable for diverse data sources such as IoT devices and server logs. The platform's ability to handle large-scale event-driven systems and dynamic workloads makes it suitable for complex streaming architectures. Despite some challenges with costs and setup complexity, Kinesis remains a popular choice for its efficient data management and processing capabilities.

What are the key features of Amazon Kinesis?

Real-time Data Streaming: Enables live data processing and analytics.
Seamless AWS Integration: Ensures smooth operation with AWS services.
High Throughput: Consistent 2Mbps rate supports large volumes of data.
Auto-scaling: Automatically adjusts to data load.
Fault Tolerance: Maintains system reliability and data integrity.
Lambda Function Processing: Processes data efficiently using Lambda.

What benefits or ROI should users expect?

Scalable Data Management: Handles data influx effortlessly.
Efficiency: Streamlines data flows without impacting performance.
Cost-effectiveness: Delivers value for budget-conscious users.
Low Latency: Provides real-time insights and reactions.
Multi-language Support: Accommodates various development needs.

In industries such as IoT, finance, and entertainment, Amazon Kinesis facilitates the real-time ingestion and processing of data streams. It connects seamlessly to data lakes and warehouses, enabling businesses to harness data-driven insights without performance loss. This capability is essential for managing dynamic workloads and large-scale event systems. By supporting tools like KDS, Firehose, and Video Streams, Kinesis empowers organizations to respond quickly to changing data environments, enhancing operational effectiveness across different sectors.

Amazon Web Services (AWS)

IBM Streams is a real-time analytics platform providing enhanced data processing capabilities for large-scale data sets, enabling enterprises to swiftly analyze and act on data-in-motion.

IBM Streams offers a robust infrastructure for processing high-velocity data, enabling the analysis and monitoring of streaming data in real time. It supports the development of applications that handle massive volumes of data with low latency. It seamlessly integrates into existing ecosystems, ensuring real-time insights are accessible across various channels. IBM Streams is especially suited for industries requiring dynamic data management capabilities.

What are the key features of IBM Streams?

Real-Time Analytics: Provides immediate data processing to offer live insights.
Scalability: Designed for handling growing data needs efficiently.
Integration: Works with other enterprise systems for data harmony.
Development Flexibility: Offers support for multiple programming languages.
Visualization Tools: Uses sophisticated tools to visualize data insights.

What benefits and ROI should users review?

Improved Decision Making: Enables quick, informed decisions based on real-time data.
Cost Efficiency: Reduces infrastructure costs by optimizing data processing.
Enhanced Data Utilization: Leverages data streams for more comprehensive insights.
Business Agility: Supports responsive business strategies through live data analysis.

In finance, IBM Streams is used for monitoring trading activities and fraud detection, ensuring compliance and reducing risk. In healthcare, it analyzes patient data streams for immediate decision-making. Retailers utilize it for inventory management and customer behavior analytics, aligning offers in real-time with customer interests.

IBM

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

Buyer's Guide

Amazon Kinesis vs. IBM Streams

September 2026

Free Report: Amazon Kinesis vs. IBM Streams

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