Amazon Kinesis vs IBM Streams comparison

Amazon Web Services (AWS) and IBM are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #5 with an average rating of 8.4, while IBM is ranked #22. Amazon Web Services (AWS) holds a 4.2% 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

3,106 Views
3,106 Comparison Views

90% willing to recommend

IBM Streams

Read 5 IBM Streams reviews

1,162 Views
953 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: April 2026).

Buyer's Guide

Amazon Kinesis vs. IBM Streams

April 2026

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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

5th

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

22nd

Average Rating

8.2

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2026, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 4.2%, down from 7.9% compared to the previous year. The mindshare of IBM Streams is 2.1%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Amazon Kinesis	4.2%
IBM Streams	2.1%
Other	93.7%

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.

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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

"What I like about Amazon Kinesis is that it's very effective for small businesses. It's a well-managed solution with excellent reporting. Amazon Kinesis is also easy to use, and even a novice developer can work with it, versus Apache Kafka, which requires expertise."

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

"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 most valuable feature is that it has a pretty robust way of capturing things."

"The Kinesis VideoStream and DataStream are the most important features."

"What turns out to be most valuable is its integration with Lambda functions because you can process the data as it comes in. As soon as data comes, you'll fire a Lambda function to process a trench of data."

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

"Before Data Streams, we were using a couple of other solutions, including Talend and Pentaho, to move data around, and the ability to have one single flow of data from multiple consumers simplified our architecture a lot, saves us a lot of time, and will help us in the future when we have to build additional applications based on the same input data."

More Amazon Kinesis pros

"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 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."

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

"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."

Cons

"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."

"The default limit that they have, which at the moment is 5,000 records per second seems too low."

"I suggest integrating additional features, such as incorporating Amazon Pinpoint or Amazon Connect as bundled offerings, rather than deploying them as separate services."

"The solution has a two-minute maximum time delay for live streaming, which could be reduced."

"Something else to mention is that we use Kinesis with Lambda a lot and the fact that you can only connect one Stream to one Lambda, I find is a limiting factor. I would definitely recommend to remove that constraint."

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

"When we had some of those slow downs, we used AWS support and I can't say that we had a great experience and they resolved the issues, but they looked into some of the flow downs and ultimately we just decided there was nothing we could do."

"I think the default settings are far too low."

More Amazon Kinesis cons

"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."

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

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

"The development IDE sometimes crashes and freezes."

Pricing and Cost Advice

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

"The tool's pricing is cheap."

"The fee is based on the number of hours the service is running."

"The pricing depends on the use cases and the level of usage. If you wanted to use Kinesis for different use cases, there's definitely a cheaper base cost involved. However, it's not entirely cheap, as different use cases might require different levels of Kinesis usage."

"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."

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

More Amazon Kinesis pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Computer Software Company

13%

Manufacturing Company

Construction Company

No data available

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

Confluent vs Amazon Kinesis

Compared 16% of the time

Apache Flink vs Amazon Kinesis

Compared 16% of the time

Azure Stream Analytics vs Amazon Kinesis

Compared 15% of the time

Redpanda vs Amazon Kinesis

Compared 9% of the time

Amazon MSK vs Amazon Kinesis

Compared 9% of the time

More Amazon Kinesis Competitors

Confluent vs IBM Streams

Compared 22% of the time

Azure Stream Analytics vs IBM Streams

Compared 22% of the time

Apache Flink vs IBM Streams

Compared 15% of the time

Google Cloud Dataflow vs IBM Streams

Compared 12% of the time

StreamAnalytix vs IBM Streams

Compared 12% of the time

More IBM Streams Competitors

Product Reports

Buyer's Guide

Amazon Kinesis

May 2026

Download Amazon Kinesis product report

Buyer's Guide

Streaming Analytics

May 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

April 2026

Free Report: Amazon Kinesis vs. IBM Streams

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