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Apache Flink vs Redpanda comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

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

Apache Flink
Ranking in Streaming Analytics
5th
Average Rating
7.8
Reviews Sentiment
7.0
Number of Reviews
17
Ranking in other categories
No ranking in other categories
Redpanda
Ranking in Streaming Analytics
15th
Average Rating
8.8
Reviews Sentiment
7.8
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Featured Reviews

Ilya Afanasyev - PeerSpot reviewer
A great solution with an intricate system and allows for batch data processing
We value this solution's intricate system because it comes with a state inside the mechanism and product. The system allows us to process batch data, stream to real-time and build pipelines. Additionally, we do not need to process data from the beginning when we pause, and we can continue from the same point where we stopped. It helps us save time as 95% of our pipelines will now be on Amazon, and we'll save money by saving time.
Vishal M Godi - PeerSpot reviewer
High-performance message brokering with excellent documentation and an easy setup
The industry standard for this kind of platform is Kafka. Confluent Kafka has acquired it. Kafka is an open-source platform built by Apache. Confluent is the commercial version of it. The major improvement of Redpanda over Kafka is firstly, good documentation. Redpanda's documentation is very easily understandable, and they have a lot of examples. In addition to that, most of the setups include using another technology called Docker, which I am very familiar with. Setting up technologies using Docker is very convenient to me, and Redpanda has provided many templates for that. Redpanda has its own built-in metrics exporter, making it easier to monitor and check performance. What makes Redpanda superior is its performance since it's written in C++. C++ is pretty much the standard for high-performance applications.

Quotes from Members

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

Pros

"Allows us to process batch data, stream to real-time and build pipelines."
"Apache Flink's best feature is its data streaming tool."
"Apache Flink is meant for low latency applications. You take one event opposite if you want to maintain a certain state. When another event comes and you want to associate those events together, in-memory state management was a key feature for us."
"This is truly a real-time solution."
"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."
"Easy to deploy and manage."
"The documentation is very good."
"With Flink, it provides out-of-the-box checkpointing and state management. It helps us in that way. When Storm used to restart, sometimes we would lose messages. With Flink, it provides guaranteed message processing, which helped us. It also helped us with maintenance or restarts."
"The cost savings have been significant."
"The UI is modern."
"What makes Redpanda superior is its performance since it's written in C++. C++ is pretty much the standard for high-performance applications."
"I tested it with ten-plus nodes, and it's highly scalable."
 

Cons

"There is a learning curve. It takes time to learn."
"Apache Flink's documentation should be available in more languages."
"The TimeWindow feature is a bit tricky. The timing of the content and the windowing is a bit changed in 1.11. They have introduced watermarks. A watermark is basically associating every data with a timestamp. The timestamp could be anything, and we can provide the timestamp. So, whenever I receive a tweet, I can actually assign a timestamp, like what time did I get that tweet. The watermark helps us to uniquely identify the data. Watermarks are tricky if you use multiple events in the pipeline. For example, you have three resources from different locations, and you want to combine all those inputs and also perform some kind of logic. When you have more than one input screen and you want to collect all the information together, you have to apply TimeWindow all. That means that all the events from the upstream or from the up sources should be in that TimeWindow, and they were coming back. Internally, it is a batch of events that may be getting collected every five minutes or whatever timing is given. Sometimes, the use case for TimeWindow is a bit tricky. It depends on the application as well as on how people have given this TimeWindow. This kind of documentation is not updated. Even the test case documentation is a bit wrong. It doesn't work. Flink has updated the version of Apache Flink, but they have not updated the testing documentation. Therefore, I have to manually understand it. We have also been exploring failure handling. I was looking into changelogs for which they have posted the future plans and what are they going to deliver. We have two concerns regarding this, which have been noted down. I hope in the future that they will provide this functionality. Integration of Apache Flink with other metric services or failure handling data tools needs some kind of update or its in-depth knowledge is required in the documentation. We have a use case where we want to actually analyze or get analytics about how much data we process and how many failures we have. For that, we need to use Tomcat, which is an analytics tool for implementing counters. We can manage reports in the analyzer. This kind of integration is pretty much straightforward. They say that people must be well familiar with all the things before using this type of integration. They have given this complete file, which you can update, but it took some time. There is a learning curve with it, which consumed a lot of time. It is evolving to a newer version, but the documentation is not demonstrating that update. The documentation is not well incorporated. Hopefully, these things will get resolved now that they are implementing it. Failure is another area where it is a bit rigid or not that flexible. We never use this for scaling because complexity is very high in case of a failure. Processing and providing the scaled data back to Apache Flink is a bit challenging. They have this concept of offsetting, which could be simplified."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"In a future release, they could improve on making the error descriptions more clear."
"The solution could be more user-friendly."
"Apache Flink should improve its data capability and data migration."
"In terms of improvement, there should be better reporting. You can integrate with reporting solutions but Flink doesn't offer it themselves."
"The version control mechanism must be improved."
"When it comes to self-hosting, their documentation could be improved."
"The command-line tools need to be improved. To quickly check the status of the topics and all."
"Recently, for the documentation, they've built their own AI chatbot, which is focused on giving you answers based on their documentation. While using that, I did not find it to be very good."
 

Pricing and Cost Advice

"The solution is open-source, which is free."
"It's an open-source solution."
"Apache Flink is open source so we pay no licensing for the use of the software."
"This is an open-source platform that can be used free of charge."
"It's an open source."
"Redpanda is cheaper than its competitors."
"It's free. Everybody can use it, only support is paid."
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Computer Software Company
15%
Manufacturing Company
7%
Healthcare Company
5%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Apache Flink?
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. ...
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?
There are more libraries that are missing and also maybe more capabilities for machine learning. It could have a friendly user interface for pipeline configuration, deployment, and monitoring.
What is your experience regarding pricing and costs for Redpanda?
Redpanda is actually a commercial platform, but they do provide free versions as well. I've been working only with the free versions.
What needs improvement with Redpanda?
Recently, for the documentation, they've built their own AI chatbot, which is focused on giving you answers based on their documentation. While using that, I did not find it to be very good. Maybe ...
What is your primary use case for Redpanda?
I have worked with Redpanda for the past two to three months. Mainly in the tech industry or software industry, there's a huge rise of streaming data. Redpanda serves as a very reliable and fast me...
 

Also Known As

Flink
No data available
 

Overview

 

Sample Customers

LogRhythm, Inc., Inter-American Development Bank, Scientific Technologies Corporation, LotLinx, Inc., Benevity, Inc.
Information Not Available
Find out what your peers are saying about Apache Flink vs. Redpanda and other solutions. Updated: April 2025.
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