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Amazon Kinesis vs Apache Flink comparison

 

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
2nd
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 March 2026, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 5.2%, down from 9.0% compared to the previous year. The mindshare of Apache Flink is 10.9%, down from 12.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Amazon Kinesis5.2%
Apache Flink10.9%
Other83.9%
Streaming Analytics
 

Featured Reviews

CD
AWS Cloud Architect at a healthcare company with 10,001+ employees
Real-time streaming and seamless integration enhance workloads with room for competitive pricing improvements
Amazon Kinesis is easy to get started with, provides good documentation, and has a multilang daemon interface that makes it programming-language agnostic. The throughput is convenient for processing volumes out of the box and does not require complex configurations. It also provides auto-scaling with different partition keys into various shards. Lambda's scalability, seamless integration with other AWS services, and support for multiple programming languages are very beneficial.
Aswini Atibudhi - PeerSpot reviewer
Distinguished AI Leader at Walmart Global Tech at Walmart
Enables robust real-time data processing but documentation needs refinement
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. It's essential to have a clear foundation; hence, it can be tough for beginners. However, once they grasp the concepts and have examples or references, it becomes easier. Intermediate users who are integrating with Kafka or other sources may find it smoother. After setting up and understanding the concepts, it becomes quite stable and scalable, allowing for customization of jobs. Every software, including Apache Flink, has room for improvement as it evolves. One key area for enhancement is user-friendliness and the developer experience; improving documentation and API specifications is essential, as they can currently be verbose and complex. Debugging and local testing pose challenges for newcomers, particularly when learning about concepts such as time semantics and state handling. Although the APIs exist, they aren't intuitive enough. We also need to simplify operational procedures, such as developing tools and tuning Flink clusters, as these processes can be quite complex. Additionally, implementing one-click rollback for failures and improving state management during dynamic scaling while retaining the last states is vital, as the current large states pose scaling challenges.

Quotes from Members

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

Pros

"The scalability is pretty good."
"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."
"Kinesis is a fully managed program streaming application. You can manage any infrastructure. It is also scalable. Kinesis can handle any amount of data streaming and process data from hundreds, thousands of processes in every source with very low latency."
"There is no problem with the tool's stability."
"The solution works well in rather sizable environments."
"The product's initial setup phase is not difficult because we are using the tool on the cloud."
"The integration capabilities of the product are good."
"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 setup was not too difficult."
"The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis."
"The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. We use Apache Flink to control our clients' installations."
"Apache Flink's best feature is its data streaming tool."
"What I appreciate best about Apache Flink is that it's open source and geared towards a distributed stream processing framework."
"Allows us to process batch data, stream to real-time and build pipelines."
"Another feature is how Flink handles its radiuses. It has something called the checkpointing concept. You're dealing with billions and billions of requests, so your system is going to fail in large storage systems. Flink handles this by using the concept of checkpointing and savepointing, where they write the aggregated state into some separate storage. So in case of failure, you can basically recall from that state and come back."
"It provides us the flexibility to deploy it on any cluster without being constrained by cloud-based limitations."
 

Cons

"Snapshot from the the from the the stream of the data analytic I have already on the cloud, do a snapshot to not to make great or to get the data out size of the web service. But to stop the process and restart a few weeks later when I have more data or more available of the client teams."
"The solution has a two-minute maximum time delay for live streaming, which could be reduced."
"I suggest integrating additional features, such as incorporating Amazon Pinpoint or Amazon Connect as bundled offerings, rather than deploying them as separate services."
"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."
"AI processing or cleaning up data would be nice since I don't think it is a feature in Amazon Kinesis right now."
"We were charged high costs for the solution’s enhanced fan-out feature."
"Kinesis can be expensive, especially when dealing with large volumes of data."
"I think the default settings are far too low."
"There is room for improvement in the initial setup process."
"The solution could be more user-friendly."
"Apache should provide more examples and sample code related to streaming to help me better adapt and utilize the tool."
"The technical support from Apache is not good; support needs to be improved. I would rate them from one to ten as not good."
"Apache Flink should improve its data capability and data migration."
"Apache Flink's documentation should be available in more languages."
"The state maintains checkpoints and they use RocksDB or S3. They are good but sometimes the performance is affected when you use RocksDB for checkpointing."
"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."
 

Pricing and Cost Advice

"It was actually a fairly high volume we were spending. We were spending about 150 a month."
"Under $1,000 per month."
"The solution's pricing is fair."
"I rate the product price a five on a scale of one to ten, where one is cheap, and ten is expensive."
"Amazon Kinesis is an expensive solution."
"The fee is based on the number of hours the service is running."
"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."
"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."
"This is an open-source platform that can be used free of charge."
"It's an open-source solution."
"It's an open source."
"The solution is open-source, which is free."
"Apache Flink is open source so we pay no licensing for the use of the software."
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Top Industries

By visitors reading reviews
Computer Software Company
16%
Financial Services Firm
14%
Manufacturing Company
7%
Educational Organization
5%
Financial Services Firm
19%
Retailer
13%
Computer Software Company
10%
Manufacturing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise10
Large Enterprise9
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise3
Large Enterprise12
 

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.
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 experience regarding pricing and costs for Apache Flink?
The solution is expensive. I rate the product’s pricing a nine out of ten, where one is cheap and ten is expensive.
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...
 

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: March 2026.
884,873 professionals have used our research since 2012.