No more typing reviews! Try our Samantha, our new voice AI agent.

Amazon Kinesis vs Apache Flink comparison

Why PeerSpot?
 

Comparison Buyer's Guide

Executive SummaryUpdated on Feb 8, 2026

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
29
Ranking in other categories
No ranking in other categories
Apache Flink
Ranking in Streaming Analytics
4th
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
19
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 Apache Flink is 7.0%, down from 14.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Apache Flink7.0%
Amazon Kinesis3.9%
Other89.1%
Streaming Analytics
 

Featured Reviews

reviewer1480695 - PeerSpot reviewer
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.
Sanjay Srivastava - PeerSpot reviewer
Software Architect at IBM
Streaming workflows have improved data integration and support real-time pipelines across platforms
We are not using Apache Flink in its advanced window capabilities. We are using the Apache Flink job in Apache SeaTunnel, meaning we can write the code inside Apache SeaTunnel. Currently, we are moving; both solutions are there. We are doing it on-premises with the help of Kubernetes and OpenShift. The main reason why Apache Flink is better is that it has more functions, and being open source with easy code in Apache SeaTunnel helps us achieve that. Cost is a major issue. I would rate the stability of the product as an eight. For Apache Flink, the final point can be rated an eight. I can recommend Apache Flink to other users for streaming support, and I am recommending it. I would rate this review an eight overall.

Quotes from Members

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

Pros

"With AWS, you don't have to invest in any kind of infrastructure."
"What I like about Amazon Kinesis is that it's very effective for small businesses. It's a well-managed solution with excellent reporting. Amazon Kinesis is also easy to use, and even a novice developer can work with it, versus Apache Kafka, which requires expertise."
"The solution works well in rather sizable environments."
"Amazon Kinesis's main purpose is to provide near real-time data streaming at a consistent 2Mbps rate, which is really impressive."
"Everything is hosted and simple."
"The scalability is pretty good, as one can have any number of nodes spawned or replicated on the primary so that any load can be handled, perhaps a few terabytes with ease in around 15 seconds."
"The major advantage with Amazon Kinesis is the availability, additionally the reliability is awesome, the replay is incredibly fast, and the ingesting, buffering, and processing of data are really fast."
"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."
"We are very happy with the product, and we have been able to achieve all of the use cases that we are expected to deliver for our customers."
"Flink moved on to becoming a standard technology for location platform."
"What I appreciate best about Apache Flink is that it's open source and geared towards a distributed stream processing framework."
"The event processing function is the most useful or the most used function. The filter function and the mapping function are also very useful because we have a lot of data to transform. For example, we store a lot of information about a person, and when we want to retrieve this person's details, we need all the details. In the map function, we can actually map all persons based on their age group. That's why the mapping function is very useful. We can really get a lot of events, and then we keep on doing what we need to do."
"The documentation is very good."
"We value this solution's intricate system because it comes with a state inside the mechanism and product, allowing us to process batch data, stream to real-time and build pipelines, and we do not need to process data from the beginning when we pause as we can continue from the same point where we stopped, helping us save time as 95% of our pipelines will now be on Amazon and we'll save money by saving time."
"This is truly a real-time solution."
"It is user-friendly and the reporting is good."
 

Cons

"Kinesis is good for Amazon Cloud but not as suitable for other cloud vendors."
"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."
"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."
"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."
"Amazon Kinesis has a less meaningful and easy use than Azure Event Hub."
"The price is not much cheaper. So, there is room for improvement in the pricing."
"The technical support could be improved. They tend to send you back to the documentation."
"The default limit that they have, which at the moment is 5,000 records per second seems too low."
"There is a learning curve. It takes time to learn."
"One way to improve Flink would be to enhance integration between different ecosystems. For example, there could be more integration with other big data vendors and platforms similar in scope to how Apache Flink works with Cloudera. Apache Flink is a part of the same ecosystem as Cloudera, and for batch processing it's actually very useful but for real-time processing there could be more development with regards to the big data capabilities amongst the various ecosystems out there."
"There are more libraries that are missing and also maybe more capabilities for machine learning."
"Failure is another area where it is a bit rigid or not that flexible."
"The solution could be more user-friendly."
"I am using the Python API and I have found the solution to be underdeveloped compared to others. There needs to be better integration with notebooks to allow for more practical development."
"Apache Flink is very powerful, but it can be challenging for beginners because it requires prior experience with similar tools and technologies, such as Kafka and batch processing."
"The technical support from Apache is not good; support needs to be improved. I would rate them from one to ten as not good."
 

Pricing and Cost Advice

"I rate the product price a five on a scale of one to ten, where one is cheap, and ten is expensive."
"It was actually a fairly high volume we were spending. We were spending about 150 a month."
"The solution's pricing is fair."
"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 product falls on a bit of an expensive side."
"The tool's pricing is cheap."
"Under $1,000 per month."
"The tool's entry price is cheap. However, pricing increases with data volume."
"It's an open-source solution."
"Apache Flink is open source so we pay no licensing for the use of the software."
"The solution is open-source, which is free."
"This is an open-source platform that can be used free of charge."
"It's an open source."
report
Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.
913,806 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
10%
Manufacturing Company
7%
Construction Company
7%
Financial Services Firm
17%
Retailer
14%
Computer Software Company
8%
Manufacturing Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise10
Large Enterprise10
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise3
Large Enterprise12
 

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?
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 u...
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 needs improvement with Apache Flink?
Apache could improve Apache Flink by providing more functionality, as they need to fully support data integration. The connectors are still very few for Apache Flink. There is a lack of functionali...
What is your primary use case for Apache Flink?
I am working with Apache Flink, which is the tool we use for data integration. Apache Flink is for data, and we are working on the data integration project, not big data, using Apache Flink and Apa...
What advice do you have for others considering Apache Flink?
We are not using Apache Flink in its advanced window capabilities. We are using the Apache Flink job in Apache SeaTunnel, meaning we can write the code inside Apache SeaTunnel. Currently, we are mo...
 

Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis
Flink
 

Overview

 

Sample Customers

Zillow, Netflix, Sonos
LogRhythm, Inc., Inter-American Development Bank, Scientific Technologies Corporation, LotLinx, Inc., Benevity, Inc.
Find out what your peers are saying about Amazon Kinesis vs. Apache Flink and other solutions. Updated: September 2026.
913,806 professionals have used our research since 2012.