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: March 2025).

Buyer's Guide

Amazon Kinesis vs. Azure Stream Analytics

March 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.

Read full review

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

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

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

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

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

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

"I have worked in companies that build tools in-house. They face scaling challenges."

"The scalability is pretty good."

"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."

More Amazon Kinesis pros

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

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

"It's scalable as a cloud product."

"I appreciate this solution because it leverages open-source technologies. It allows us to utilize the latest streaming solutions and it's easy to develop."

"It was easy for me to use from the beginning. I am accustomed to working with Microsoft."

"Technical support is pretty helpful."

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

"Provides deep integration with other Azure resources."

More Azure Stream Analytics pros

Cons

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

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

"Kinesis Data Analytics needs to be improved somewhat. It's SQL based data but it is not as user friendly as MySQL or Athena tools."

"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 services which are described in the documentation could use some visual presentation because for someone who is new to the solution the documentation is not easy to follow or beginner friendly and can leave a person feeling helpless."

"Amazon Kinesis involved a more complex setup and configuration than Azure Event Hub."

"Kinesis is good for Amazon Cloud but not as suitable for other cloud vendors."

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

More Amazon Kinesis cons

"There are too many products in the Azure landscape, which sometimes leads to overlap between them."

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

"More flexibility in terms of writing queries and accommodating additional facilities would be beneficial."

"The UI should be a little bit better from a usability perspective."

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

"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."

"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."

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

More Azure Stream Analytics cons

Pricing and Cost Advice

"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 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."

"Under $1,000 per month."

"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."

"Amazon Kinesis is an expensive solution."

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

"The tool's pricing is cheap."

More Amazon Kinesis pricing and cost advice

"The cost of this solution is less than competitors such as Amazon or Google Cloud."

"The current price is substantial."

"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."

"Azure Stream Analytics is a little bit expensive."

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

"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

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

Confluent vs Amazon Kinesis

Compared 31% 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 27% 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

March 2025

Download Amazon Kinesis product report

Buyer's Guide

Azure Stream Analytics

March 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

March 2025

Free Report: Amazon Kinesis vs. Azure Stream Analytics

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