Amazon Kinesis vs Azure Stream Analytics comparison

Amazon Web Services (AWS) and Microsoft are both solutions in the Streaming Analytics category. Amazon Web Services (AWS) is ranked #2 with an average rating of 7.8, while Microsoft is ranked #3 with an average rating of 7.9. Amazon Web Services (AWS) holds a 8.7% mindshare in SA, compared to Microsoft’s 10.4% mindshare. Additionally, 89% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 92% of Microsoft users who would recommend it.

Amazon Kinesis

Read 27 Amazon Kinesis reviews

5,675 Views
4,237 Comparison Views

89% willing to recommend

Azure Stream Analytics

Read 26 Azure Stream Analytics reviews

4,867 Views
4,124 Comparison Views

92% willing to recommend

Amazon Kinesis

Azure Stream Analytics

Comparison Buyer's Guide

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Executive SummaryUpdated on Mar 23, 2025

Azure Stream Analytics and Amazon Kinesis compete in the data streaming category. Amazon Kinesis has the advantage due to its simplicity and cost-effectiveness for smaller use cases.

Features: Azure Stream Analytics benefits from integration with Azure resources, real-time analytics with Power BI, and IoT hub integration. Amazon Kinesis offers automatic scaling, data transformation capabilities, and ease of management with AWS hosting.

Room for Improvement: Azure Stream Analytics needs clearer pricing, enhanced error logging, and improved Power BI integration. Amazon Kinesis could enhance sharding scalability, make Kinesis Analytics more user-friendly, and improve technical documentation.

Ease of Deployment and Customer Service: Azure Stream Analytics supports various cloud deployments, with varying support experiences. Amazon Kinesis supports public cloud deployment, with straightforward setup but depends on user initiative for problem-solving.

Pricing and ROI: Azure Stream Analytics charges per streaming unit, making it complex and costly at scale, but offers value for those using Azure services. Amazon Kinesis is cost-effective, particularly for smaller projects, with pricing based on usage levels.

To learn more, read our detailed Amazon Kinesis vs. Azure Stream Analytics Report (Updated: April 2025).

Buyer's Guide

Amazon Kinesis vs. Azure Stream Analytics

April 2025

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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

2nd

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Azure Stream Analytics

Ranking in Streaming Analytics

3rd

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 8.7%, down from 13.9% compared to the previous year. The mindshare of Azure Stream Analytics is 10.4%, down from 12.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

Rajni Kumar Jha

Senior Software Engineer at JPMorgan Chase & Co.

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.

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SantiagoCordero

Director, Governance & Infrastructure & Director at VASS

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.

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

"Its scalability is very high. There is no maintenance and there is no throughput latency. I think data scalability is high, too. You can ingest gigabytes of data within seconds or milliseconds."

"The management and analytics are valuable features."

"Everything is hosted and simple."

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

"I like the ease of use and how we can quickly get the configurations done, making it pretty straightforward and stable."

"There is no problem with the tool's stability."

"Amazon Kinesis also provides us with plenty of flexibility."

"The product's initial setup phase is not difficult because we are using the tool on the cloud."

More Amazon Kinesis pros

"The most valuable features are the IoT hub and the Blob storage."

"It provides the capability to streamline multiple output components."

"The solution's most valuable feature is its ability to create a query using SQ."

"We find the query editor feature of this solution extremely valuable for our business."

"It's easy to implement and maintain pipelines with minimal complexity."

"I like the IoT part. We have mostly used Azure Stream Analytics services for it"

"Any time I needed assistance, they were helpful."

"The life cycle, report management and crash management features are great."

More Azure Stream Analytics pros

Cons

"The price is not much cheaper. So, there is room for improvement in the pricing."

"One area for improvement in the solution is the file size limitation of 10 Mb. My company works with files with a larger file size. The batch size and throughput also need improvement in Amazon Kinesis."

"In order to do a successful setup, the person handling the implementation needs to know the solution very well. You can't just come into it blind and with little to no experience."

"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."

"If there were better documentation on optimal sharding strategies then it would be helpful."

"It would be beneficial if Amazon Kinesis provided document based support on the internet to be able to read the data from the Kinesis site."

"Amazon Kinesis should improve its limits."

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

More Amazon Kinesis cons

"Early in the process, we had some issues with stability."

"We would like to have centralized platform altogether since we have different kind of options for data ingestion. Sometimes it gets difficult to manage different platforms."

"If something goes wrong, it's very hard to investigate what caused it and why."

"Azure Stream Analytics is challenging to customize because it's not very flexible."

"Easier scalability and more detailed job monitoring features would be helpful."

"Sometimes when we connect Power BI, there is a delay or it throws up some errors, so we're not sure."

"Azure Stream Analytics could improve by having clearer metrics as to the scale, more metrics around the data set size that is flowing through it, and performance tuning recommendations."

"The only challenge was that the streaming analytics area in Azure Stream Analytics could not meet our company's expectations, making it a component where improvements are required."

More Azure Stream Analytics cons

Pricing and Cost Advice

"Amazon Kinesis is an expensive solution."

"Under $1,000 per month."

"I rate the product price a five on a scale of one to ten, where one is cheap, and ten is expensive."

"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 tool's pricing is cheap."

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

"The solution's pricing is fair."

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

More Amazon Kinesis pricing and cost advice

"The current price is substantial."

"The product's price is at par with the other solutions provided by the other cloud service providers in the market."

"Azure Stream Analytics is a little bit expensive."

"We pay approximately $500,000 a year. It's approximately $10,000 a year per license."

"I rate the price of Azure Stream Analytics a four out of five."

"The licensing for this product is payable on a 'pay as you go' basis. This means that the cost is only based on data volume, and the frequency that the solution is used."

"There are different tiers based on retention policies. There are four tiers. The pricing varies based on steaming units and tiers. The standard pricing is $10/hour."

"When scaling up, the pricing for Azure Stream Analytics can get relatively high. Considering its capabilities compared to other solutions, I would rate it a seven out of ten for cost. However, we've found ways to optimize costs using tools like Databricks for specific tasks."

More Azure Stream Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

18%

Financial Services Firm

17%

Manufacturing Company

10%

Retailer

Computer Software Company

15%

Financial Services Firm

14%

Manufacturing Company

10%

Retailer

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.

See all answers

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.

See all answers

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...

See all answers

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...

See all answers

What is your experience regarding pricing and costs for Azure Stream Analytics?

I have no problem with pricing. We sell the data analytics value and operational value to customers, focusing on productivity and efficiency from the cloud, rather than just the infrastructure or p...

See all answers

What needs improvement with Azure Stream Analytics?

There is a lack of technical support from Microsoft's local office, particularly in Taiwan. We often have to learn online, and language can be a communication barrier since not many IT staff can sp...

See all answers

Comparisons

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Compared 30% of the time

Apache Flink vs Amazon Kinesis

Compared 17% of the time

Amazon MSK vs Amazon Kinesis

Compared 9% of the time

Databricks vs Amazon Kinesis

Compared 6% of the time

Google Cloud Dataflow vs Amazon Kinesis

Compared 5% of the time

More Amazon Kinesis Competitors

Databricks vs Azure Stream Analytics

Compared 26% of the time

Amazon MSK vs Azure Stream Analytics

Compared 23% of the time

Apache Flink vs Azure Stream Analytics

Compared 16% of the time

Confluent vs Azure Stream Analytics

Compared 4% of the time

Apache Spark vs Azure Stream Analytics

Compared 4% of the time

More Azure Stream Analytics Competitors

Product Reports

Buyer's Guide

Amazon Kinesis

April 2025

Download Amazon Kinesis product report

Buyer's Guide

Azure Stream Analytics

April 2025

Download Azure Stream Analytics product report

Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis

ASA

Overview

Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.

Amazon Web Services (AWS)

Azure Stream Analytics is a robust real-time analytics service that has been designed for critical business workloads. Users are able to build an end-to-end serverless streaming pipeline in minutes. Utilizing SQL, users are able to go from zero to production with a few clicks, all easily extensible with unique code and automatic machine learning abilities for the most advanced scenarios.

Azure Stream Analytics has the ability to analyze and accurately process exorbitant volumes of high-speed streaming data from numerous sources at the same time. Patterns and scenarios are quickly identified and information is gathered from various input sources, such as social media feeds, applications, clickstreams, sensors, and devices. These patterns can then be implemented to trigger actions and launch workflows, such as feeding data to a reporting tool, storing data for later use, or creating alerts. Azure Stream Analytics is also offered on Azure IoT Edge runtime, so the data can be processed on IoT devices.

Top Benefits

User friendly: Azure Stream Analytics is very straightforward and easy to use. Out of the box and with a few clicks, users are able to connect to numerous sources and sinks, and easily develop an end-to-end pipeline. Stream Analytics can easily connect to Azure IoT Hub and Azure Event Hub for streaming ingestion, in addition to connecting with Azure Blob storage for historical data ingestion.
Flexible deployment: For low-latency analytics, Azure Stream Analytics can run on Azure Stack or IoT edge. For large-scale analytics, the solution can run in the cloud. Azure Stream Analytics uses the same query language and tools for both the cloud and the edge, facilitating an easier process for developers to design exceptional hybrid architectures for streaming processes.
Cost-effective: With Azure Stream Analytics, users only pay for the streaming units they consume; there are no upfront costs. Users can easily scale up or down as needed; there is no commitment or cluster provisioning.
Trustworthy: Azure Stream Analytics guarantees event processing to be 99.99% available with a minute level of granularity. Azure Stream Analytics has embedded recovery capabilities and checkpoints to keep things running smoothly at all times. Events are never lost with Azure Stream Analytics at-least once delivery of events and exactly one event processing.

Reviews from Real Users

“Azure Stream Analytics is something that you can use to test out streaming scenarios very quickly in the general sense and it is useful for IoT scenarios. If I was to do a project with IoT and I needed a streaming solution, Azure Stream Analytics would be a top choice. The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex.” - Olubisi A., Team Lead at a tech services company.

“It's used primarily for data and mining - everything from the telemetry data side of things. It's great for streaming and makes everything easy to handle. The streaming from the IoT hub and the messaging are aspects I like a lot.” - Sudhendra U., Technical Architect at Infosys

Microsoft

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

Buyer's Guide

Amazon Kinesis vs. Azure Stream Analytics

April 2025

Free Report: Amazon Kinesis vs. Azure Stream Analytics

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