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Apache Flink vs Apache Pulsar comparison

 

Comparison Buyer's Guide

Executive Summary

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
6th
Average Rating
7.6
Reviews Sentiment
6.9
Number of Reviews
16
Ranking in other categories
No ranking in other categories
Apache Pulsar
Ranking in Streaming Analytics
18th
Average Rating
8.0
Reviews Sentiment
6.2
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the Streaming Analytics category, the mindshare of Apache Flink is 13.2%, up from 9.5% compared to the previous year. The mindshare of Apache Pulsar is 2.0%, up from 1.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

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.
it_user1087029 - PeerSpot reviewer
The solution can mimic other APIs without changing a line of code
The solution operates as a classic message broker but also as a streaming platform. It operates differently than a traditional streaming platform with storage and computing handled separately. It scales easier and better than Kafka which can be stubborn. You can even make it act like Kafka because it understands Kafka APIs. There are even companies that will sell you Kafka but underneath it is Apache Pulsar. The solution is very compatible because it can mimic other APIs without changing a line of code.

Quotes from Members

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

Pros

"Apache Flink's best feature is its data streaming tool."
"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."
"Allows us to process batch data, stream to real-time and build pipelines."
"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."
"Easy to deploy and manage."
"Apache Flink offers a range of powerful configurations and experiences for development teams. Its strength lies in its development experience and capabilities."
"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."
"It is user-friendly and the reporting is good."
"The solution operates as a classic message broker but also as a streaming platform."
 

Cons

"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."
"In a future release, they could improve on making the error descriptions more clear."
"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."
"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."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"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."
"In terms of stability with Flink, it is something that you have to deal with every time. Stability is the number one problem that we have seen with Flink, and it really depends on the kind of problem that you're trying to solve."
"Documentation is poor because much of it is in Chinese with no English translation."
 

Pricing and Cost Advice

"It's an open source."
"This is an open-source platform that can be used free of charge."
"Apache Flink is open source so we pay no licensing for the use of the software."
"The solution is open-source, which is free."
"It's an open-source solution."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
24%
Computer Software Company
15%
Manufacturing Company
7%
Healthcare Company
5%
Computer Software Company
21%
Financial Services Firm
8%
Manufacturing Company
8%
Comms Service Provider
6%
 

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.
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Also Known As

Flink
No data available
 

Overview

 

Sample Customers

LogRhythm, Inc., Inter-American Development Bank, Scientific Technologies Corporation, LotLinx, Inc., Benevity, Inc.
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