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Amazon Kinesis vs Azure Stream Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jun 29, 2025

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 cost savings, seamless integration, improved monitoring, and reduces data ingestion costs, enhancing ROI and architecture.
Sentiment score
6.1
Azure Stream Analytics offers quick, cost-effective deployment, resulting in positive ROI and customer satisfaction for non-complex scenarios.
With Lambda, there is no need for data transfer charges, which is beneficial for less frequent workloads.
 

Customer Service

Sentiment score
7.1
Amazon Kinesis customer support is generally quick and effective, but experiences vary in technical guidance and response times.
Sentiment score
6.5
Azure Stream Analytics support is effective and responsive, with service quality varying by subscription and occasional communication challenges.
We receive prompt support from AWS solution architects or TAMs.
The support on critical issues depends on the level of subscription that you have with Microsoft itself.
They've managed to answer all my questions and provide help in a timely manner.
There is a big communication gap due to lack of understanding of local scenarios and language barriers.
 

Scalability Issues

Sentiment score
7.3
Amazon Kinesis is scalable for reliable streaming, but complex processing and costs may vary with implementation and data volumes.
Sentiment score
7.5
Azure Stream Analytics is highly scalable, cloud-based, easily integrated, adaptable, and efficiently manages varying workloads, despite some cost concerns.
Amazon Kinesis provides auto-scaling with streams that handle large volumes well.
Maintenance requires a couple of people, however, it's not a full-time endeavor.
Azure Stream Analytics is scalable, and I would rate it seven out of ten.
 

Stability Issues

Sentiment score
7.8
Amazon Kinesis is praised for stability and fault tolerance, though some users report slowdowns and capacity issues.
Sentiment score
6.5
Azure Stream Analytics is reliable but can face downtime, bugs, transformation challenges, and requires tuning for optimal stability.
They require significant effort and fine-tuning to function effectively.
 

Room For Improvement

Amazon Kinesis requires improvements in throughput, automation, setup complexity, data retention, machine learning features, and user-friendly interfaces.
Azure Stream Analytics needs better pricing, logging, customization, connectivity, integration, UI, flexibility, support, error handling, and simplified licensing.
Amazon Kinesis could improve its pricing to be more competitive, especially for large volumes.
Any coding challenges they face can be helped by the implementation of AI within the tool itself, such as using chatbots for assistance, automated testing, and code formatting.
A cost comparison between products is also not straightforward.
There is a lack of technical support from Microsoft's local office, particularly in Taiwan.
 

Setup Cost

Amazon Kinesis is cost-effective compared to self-managed solutions, but prices can increase with high data usage and features.
Azure Stream Analytics offers competitive pricing but can be costly for enterprises; users find billing reports confusing.
Amazon Kinesis and Lambda pricing is competitive, but we noticed that scaling and large volumes could potentially increase costs significantly.
From my point of view, it should be cheaper now, considering the years since its release.
We sell the data analytics value and operational value to customers, focusing on productivity and efficiency from the cloud.
Regarding the cost of Azure Stream Analytics, I believe the price is reasonable for the tool.
 

Valuable Features

Amazon Kinesis offers easy configuration, real-time analytics, and robust AWS integration, ideal for managing large, complex data workflows.
Azure Stream Analytics provides integrated, scalable real-time analytics with SQL queries and machine learning, enhancing data processing capabilities efficiently.
Lambda's scalability, seamless integration with other AWS services, and support for multiple programming languages are very beneficial.
It's very accurate and uses existing technologies in terms of writing queries, utilizing standard query languages such as SQL, Spark, and others to provide information.
Clients can choose and subscribe to the service items they need, making it more flexible than IBM solutions, especially in data analytics or data governance.
The native connectors and integration with other Microsoft products.
 

Categories and Ranking

Amazon Kinesis
Ranking in Streaming Analytics
2nd
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
28
Ranking in other categories
No ranking in other categories
Azure Stream Analytics
Ranking in Streaming Analytics
3rd
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
28
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2025, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 8.0%, down from 12.6% compared to the previous year. The mindshare of Azure Stream Analytics is 9.2%, down from 12.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Prabin Silwal - PeerSpot reviewer
Pipeline setup is very simple
I am not exactly sure about where improvements are needed in the tool. When I was working on the tool, it was very scalable, and the only thing we needed in our company was temporary streaming stuff that could work well. We didn't want to set up our own Kafka, other queues, or processing systems. As it is a cloud tool, it is easy for us to use the tool, and it satisfies all our requirements. Maybe for the other cases, if we need, then it may need some improvements. The tool satisfies our particular needs. Currently, the pipeline setup is very simple. For our particular use cases, it is because we just want to get the data and send it to the different data lakes or some logging system. Previously, we also used Amazon Kinesis to log those to Splunk, and later on, we removed Splunk and transferred that to Datadog. For our use cases, I don't want any new features in the tool. Amazon Kinesis' use case is for collecting, processing, and analyzing. If anything can be added to the tool, then I feel one should be able to use the same kind of tool so that everything is there in the product, like an alert system, and so that one can analyze, make a query, and do sourcing from the solution itself rather than using other logging and monitoring systems. The tool should focus on having an alert system rather than having to use a third-party solution. We can just get the data over Amazon Kinesis, and we can directly use all the benefits of current analytical tools, like in the areas involving BI, Looker, and Tableau. One would not need to buy the aforementioned tools, and we can just get started with Amazon Kinesis.
SantiagoCordero - PeerSpot reviewer
Native connectors and integration simplify tasks but portfolio complexity needs addressing
There are too many products in the Azure landscape, which sometimes leads to overlap between them. Microsoft continuously releases new products or solutions, which can be frustrating when determining the appropriate features from one solution over another. A cost comparison between products is also not straightforward. They should simplify their portfolio. The Microsoft licensing system is confusing and not easy to understand, and this is something they should address. In the future, I may stop using Stream Analytics and move to other solutions. I discussed Palantir earlier, which is something I want to explore in depth because it allows me to accomplish more efficiently compared to solely using Azure. Additionally, the vendors should make the solution more user-friendly, incorporating low-code and no-code features. This is something I wish to explore further.
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Top Industries

By visitors reading reviews
Computer Software Company
17%
Financial Services Firm
17%
Manufacturing Company
10%
Educational Organization
5%
Financial Services Firm
15%
Computer Software Company
14%
Manufacturing Company
9%
Retailer
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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 and Lambda pricing is competitive, but we noticed that scaling and large volumes could potentially increase costs significantly.
What needs improvement with Amazon Kinesis?
Amazon Kinesis could improve its pricing to be more competitive, especially for large volumes. Also, the KCL library's documentation could be improved to better explain the configuration parameters...
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
What is your experience regarding pricing and costs for Azure Stream Analytics?
The solution does not need any license; it comes with your subscription.
What needs improvement with Azure Stream Analytics?
It does not always give you the right reason or the correct reason. For example, if a service is stopped, it just tells you that it stopped and started. It does not give you any good insight as to ...
 

Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis
ASA
 

Overview

 

Sample Customers

Zillow, Netflix, Sonos
Rockwell Automation, Milliman, Honeywell Building Solutions, Arcoflex Automation Solutions, Real Madrid C.F., Aerocrine, Ziosk, Tacoma Public Schools, P97 Networks
Find out what your peers are saying about Amazon Kinesis vs. Azure Stream Analytics and other solutions. Updated: July 2025.
864,053 professionals have used our research since 2012.