Amazon Kinesis vs Confluent comparison

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Amazon Kinesis

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Executive SummaryUpdated on Feb 8, 2026

Confluent and Amazon Kinesis compete in real-time data streaming platforms. While Confluent is praised for its flexibility, Amazon Kinesis offers scalability and AWS integration.

Features: Confluent offers a robust Kafka ecosystem with stream processing, strong security, and multi-cloud capabilities. It provides versatility for various data workloads. Amazon Kinesis supports seamless AWS integration, enabling reliable large-scale streaming applications. Its real-time data ingestion and analytics are noteworthy features.

Room for Improvement: Confluent could enhance AWS integration to match the seamless experience Kinesis offers. Its infrastructure automation could also be improved. Additionally, more intuitive tooling for deployment might benefit users. Amazon Kinesis could benefit from a more user-friendly interface akin to Confluent's. It might also streamline its pricing structure and improve support for non-AWS services.

Ease of Deployment and Customer Service: Confluent simplifies deployment with intuitive configurations and strong customer support, appealing to teams with diverse technical expertise. Amazon Kinesis provides comprehensive AWS documentation and resource access, yet it may require specific AWS knowledge for optimal usage.

Pricing and ROI: Confluent offers competitive pricing with predictable costs, suitable for Kafka-centric companies. Amazon Kinesis may be costlier due to AWS integration but provides high ROI for businesses leveraging AWS services, due to its robust capabilities.

To learn more, read our detailed Amazon Kinesis vs. Confluent Report (Updated: September 2026).

Amazon Kinesis vs. Confluent

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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

12th

Average Rating

8.0

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Confluent

Ranking in Streaming Analytics

7th

Average Rating

8.2

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of September 2026, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 3.9%, down from 7.0% compared to the previous year. The mindshare of Confluent is 6.3%, down from 8.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Confluent	6.3%
Amazon Kinesis	3.9%
Other	89.8%

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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PavanManepalli

AVP - Sr Middleware Messaging Integration Engineer at Wells Fargo

Has supported streaming use cases across data centers and simplifies fraud analytics with SQL-based processing

I recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about Confluent charging high fees while not offering features that match those of other tools. They need to improve in that direction by not only reducing costs but also providing better solutions for the problems customers face to avoid frustrations, whether through future enhancement requests or ensuring product stability. The cost should be worked on, and they should provide better solutions for customers. Solutions should focus on hierarchical topics; if a customer has different types of data and sources, they should be able to send them to the same place for analytics. Currently, Confluent requires everything to send to the same topic, which becomes very large and makes running analytics difficult. The hierarchy of topics should be improved. This part is available in MQ and other products such as Solace, but it is missing in Confluent, leading many in capital markets and trading to switch to Solace. In terms of stability, it is not the stability itself that needs improvement but rather the delivery semantics. Other products offer exactly-once delivery out of the box, whereas Confluent states it will offer this but lacks the knobs or levers for tuning configurations effectively. Confluent has hundreds of configurations that application teams must understand, which creates a gap. Users are often unaware of what values to set for better performance or to achieve exactly-once semantics, making it difficult to navigate through them. Delivery semantics also need to be worked on.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"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."

"I find data Firehose and data streams are much more intelligent than other streaming solutions."

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

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

"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."

"Kinesis replaced a whole tier of servers, so we didn't need to have a server to catch the data and then send the data somewhere else, because Kinesis was the input port for very large amounts of data."

"Compared to what we were doing with Kafka, which was taking about 30% just to keep things together, with Kinesis I think we're probably saving tens of thousands, if not $100,000 per year."

"We have been able to drop our costs for ingesting data by about 60 to 70%."

More Amazon Kinesis pros

"The monitoring module is impressive."

"The design of the product is extremely well built and it is highly configurable."

"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."

"Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance."

"The documentation process is fast with the tool."

"Having used SharePoint in the past, when I compare with traditional, old document repositories, like SharePoint, I would definitely recommend Confluent."

"The client APIs are the most valuable feature."

"I would rate the scalability of the solution at eight out of ten. We have 20 people who use Confluent in our organization now, and we hope to increase usage in the future."

More Confluent pros

Cons

"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."

"One thing that would be nice would be a policy for increasing the number of Kinesis streams because that's the one thing that's constant. You can change it in real time, but somebody has to change it, or you have to set some kind of meter. So, auto-scaling of adding and removing streams would be nice."

"Amazon Kinesis has a less meaningful and easy use than Azure Event Hub."

"Kinesis can be expensive, especially when dealing with large volumes of data."

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

"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."

"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."

More Amazon Kinesis cons

"It requires some application specific connectors which are lacking. This needs to be added."

"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."

"The formatting aspect within the page can be improved and more powerful."

"Confluent's price needs improvement."

"There is no local support team in Saudi Arabia."

"I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team."

"The pricing model should include the ability to pick features and be charged for them only."

"The Schema Registry service could be improved. I would like a bigger knowledge base of other use cases and more technical forums. It would be good to have more flexible monitoring features added to the next release as well."

More Confluent cons

Pricing and Cost Advice

"I think for us, with Amazon Kinesis, if we have to set up our own Kafka or cluster, it will be very time-consuming. If one considers the aforementioned aspect, Amazon Kinesis is a cheap tool."

"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."

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

"The tool's pricing is cheap."

"Amazon Kinesis is an expensive solution."

"The solution's pricing is fair."

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

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

More Amazon Kinesis pricing and cost advice

"Confluent is highly priced."

"Regarding pricing, I think Confluent is a premium product, but it's hard for me to say definitively if it's overly expensive. We're still trying to understand if the features and reduced maintenance complexity justify the cost, especially as we scale our platform use."

"You have to pay additional for one or two features."

"Confluent has a yearly license, which is a bit high because it's on a per-user basis."

"Confluence's pricing is quite reasonable, with a cost of around $10 per user that decreases as the number of users increases. Additionally, it's worth noting that for teams of up to 10 users, the solution is completely free."

"Confluent is an expensive solution as we went for a three contract and it was very costly for us."

"The solution is cheaper than other products."

"The pricing model of Confluent could improve because if you have a classic use case where you're going to use all the features there is no plan to reduce the features. You should be able to pick and choose basic services at a reduced price. The pricing was high for our needs. We should not have to pay for features we do not use."

More Confluent pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

10%

Manufacturing Company

Construction Company

Financial Services Firm

14%

Retailer

12%

Manufacturing Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	10
Large Enterprise	10

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	4
Large Enterprise	17

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.

What needs improvement with Amazon Kinesis?

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...

What is your experience regarding pricing and costs for Confluent?

They charge a lot for scaling, which makes it expensive.

What needs improvement with Confluent?

What is your primary use case for Confluent?

The main use cases for Confluent are log aggregation and streaming. I'm familiar with Confluent stream processing with KSQL. KSQL helps in terms of data analytics strategies because if we are the d...

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Product Reports

Amazon Kinesis

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Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis

No data available

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)

Confluent offers scalable, open-source flexibility and seamless data replication, supported by strong cloud integration. Key features like Kafka Connect and real-time processing make it valuable for data streaming projects while ensuring high availability with a Multi-Region Cluster.

Confluent is a robust data streaming platform that enables efficient management and integration of real-time data pipelines. Its message-driven architecture and fault tolerance provide reliability, while a user-friendly dashboard and connectors support diverse data sources. Cloud integration reduces costs, and extensive documentation, plugins, and monitoring capabilities enhance collaboration and revision management. Despite some areas needing improvement, including security in the SaaS version and integration flexibility, Confluent remains a staple in industries requiring vast data processing and task automation.

What are Confluent's key features?

Scalability: Handles large volumes of data, ensuring continuous performance.
Kafka Connect: Enables seamless data integration across multiple systems.
Real-time Processing: Facilitates instant data insights for rapid decision-making.
Multi-Region Cluster: Maintains data availability across different geographical locations.
Cloud Integration: Reduces operational costs and enhances deployment flexibility.
User Dashboard: Simplifies management with an intuitive interface.

What benefits and ROI should users consider in reviews?

Cost-Efficiency: Improved processes reduce operational expenses.
Data Reliability: Ensures consistent and accurate data handling.
Increased Collaboration: Boosts team efficiency with comprehensive documentation and management tools.
Scalability: Supports business growth without compromising performance.
Integration Flexibility: Seamlessly connects with diverse data sources and systems.

Confluent is commonly implemented in finance, insurance, and software industries for applications like fraud detection, ETL tasks, and enterprise communication. It supports real-time data processing, project management, and task automation, often integrating with project management tools like Jira, providing valuable solutions for business processes.

Sample Customers

Zillow, Netflix, Sonos

ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost

Amazon Kinesis vs. Confluent