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 7.9, while Microsoft is ranked #4 with an average rating of 8.1. Amazon Web Services (AWS) holds a 9.1% mindshare in SA, compared to Microsoft’s 11.4% 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

7,426 Views
5,574 Comparison Views

89% willing to recommend

Azure Stream Analytics

Read 25 Azure Stream Analytics reviews

6,265 Views
5,355 Comparison Views

92% willing to recommend

Amazon Kinesis

Azure Stream Analytics

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

Azure Stream Analytics and Amazon Kinesis compete in the real-time data analytics category. Azure Stream Analytics has a slight edge for those integrated within Azure's ecosystem, while Amazon Kinesis offers superior flexibility and scalability across diverse environments.

Features: Azure Stream Analytics integrates deeply with Azure's ecosystem, supports real-time analytics, and excels in IoT hub connectivity. Amazon Kinesis is known for its straightforward use, flexible integrations with services like S3, and efficient handling of large-scale data streaming.

Room for Improvement: Azure Stream Analytics faces limitations with flexible use outside Azure, real-time data joins complexity, and intricate pricing. Amazon Kinesis is hindered by partitioning limits, pricing complexities for high volumes, and a need for enhanced monitoring capabilities.

Ease of Deployment and Customer Service: Both Azure Stream Analytics and Amazon Kinesis offer cloud-based scalability. Azure's support is praised for Microsoft technology users, while Amazon Kinesis is appreciated for its straightforward community support, though some users encounter specific technical challenges.

Pricing and ROI: Azure Stream Analytics is seen as expensive but potentially valuable for enterprises with complex needs, offering positive ROI due to quick deployment. Amazon Kinesis is favored for cost-effectiveness and operational cost savings, making it slightly more advantageous for many scenarios.

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

Buyer's Guide

Amazon Kinesis vs. Azure Stream Analytics

January 2025

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Helped 832,138 peers since 2012

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

4th

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2025, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 9.1%, down from 14.3% compared to the previous year. The mindshare of Azure Stream Analytics is 11.4%, down from 12.9% 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

Sudhendra Umarji

Technical Architect at Infosys

Easy to set up and user-friendly, but could be priced better

I haven't come across missing items. It does what I need it to do. The pricing is a little bit high. The UI should be a little bit better from a usability perspective. The endpoint, if you are outsourcing to a third party, should have easier APIs. I'd like to have more destination sources available to us.

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

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

"The feature that I've found most valuable is the replay. That is one of the most valuable in our business. We are business-to-business so replay was an important feature - being able to replay for 24 hours. That's an important feature."

"The solution's technical support is flawless."

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

"The scalability is pretty good."

"Amazon Kinesis has improved our ROI."

"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."

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

More Amazon Kinesis pros

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

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

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

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

"We use Azure Stream Analytics for simulation and internal activities."

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

"The way it organizes data into tables and dashboards is very helpful."

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

More Azure Stream Analytics pros

Cons

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

"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."

"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."

"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."

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

"Amazon Kinesis should improve its limits."

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

"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."

More Amazon Kinesis cons

"I would like to have a contact individual at Microsoft."

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

"The solution could be improved by providing better graphics and including support for UI and UX testing."

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

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

"The solution doesn't handle large data packets very efficiently, which could be improved upon."

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

"Its features for event imports and architecture could be enhanced."

More Azure Stream Analytics cons

Pricing and Cost Advice

"The solution's pricing is fair."

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

"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 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."

"Amazon Kinesis is an expensive solution."

"Under $1,000 per month."

"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."

More Amazon Kinesis pricing and cost advice

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

"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."

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

"The current price is substantial."

"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."

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

More Azure Stream Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

18%

Manufacturing Company

10%

Retailer

Computer Software Company

15%

Financial Services Firm

14%

Manufacturing Company

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?

Stream Analytics is cheaper, especially for small-scale requirements or telemetry needs. However, for enterprise-level data handling, structured streaming with Databricks might be more cost-effecti...

See all answers

What needs improvement with Azure Stream Analytics?

More flexibility in terms of writing queries and accommodating additional facilities would be beneficial. The complexity of handling messages that need decoding and contain different characters sho...

See all answers

Comparisons

Confluent vs Amazon Kinesis

Compared 26% of the time

Apache Flink vs Amazon Kinesis

Compared 15% of the time

Amazon MSK vs Amazon Kinesis

Compared 13% of the time

Google Cloud Dataflow vs Amazon Kinesis

Compared 5% of the time

Apache Spark Streaming vs Amazon Kinesis

Compared 5% of the time

More Amazon Kinesis Competitors

Databricks vs Azure Stream Analytics

Compared 28% of the time

Amazon MSK vs Azure Stream Analytics

Compared 21% of the time

Apache Flink vs Azure Stream Analytics

Compared 14% of the time

Apache Spark vs Azure Stream Analytics

Compared 5% of the time

Confluent vs Azure Stream Analytics

Compared 4% of the time

More Azure Stream Analytics Competitors

Product Reports

Buyer's Guide

Amazon Kinesis

February 2025

Download Amazon Kinesis product report

Buyer's Guide

Azure Stream Analytics

February 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

January 2025

Free Report: Amazon Kinesis vs. Azure Stream Analytics

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