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Confluent vs IBM Cloud Pak for Integration 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

Confluent
Average Rating
8.2
Reviews Sentiment
6.7
Number of Reviews
23
Ranking in other categories
Streaming Analytics (4th)
IBM Cloud Pak for Integration
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
5
Ranking in other categories
API Management (26th), Cloud Data Integration (15th)
 

Featured Reviews

Gustavo-Barbosa Dos Santos - PeerSpot reviewer
Has good technical support services and a valuable feature for real-time data streaming
Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance. It helps us understand the various requirements of multiple customers and validates the information for different versions. We can automate the tasks using Confluent Kafka. Thus, it guarantees us the data quality and maintains the integrity of message contracts.
Igor Khalitov - PeerSpot reviewer
Manages APIs and integrates microservices with redirection feature
IBM Cloud Pak for Integration includes monitoring capabilities to track the performance and health of your integrations. You can quickly roll back to a previous version if an issue arises. Additionally, it supports incremental deployments, allowing you to shift traffic to a new version of an API gradually. For example, you can start by directing 10% of traffic to the new version while the rest continue using the legacy version. If everything works as expected, you can gradually increase the traffic to the new version over time. IBM Cloud Pak for Integration has a client base that includes numerous organizations using AI and machine learning technologies. We leverage an open-source machine learning framework and integrate it with Kafka to help create and manage various products and data retrieval processes. For companies with private data, the framework first retrieves relevant data from a GitHub database, which is then combined with the final request before being sent to a language model like GPT. This ensures that the language model uses your specific data to generate responses. Kafka plays a key role by streaming real-time data from file systems and databases like Oracle and Microsoft SQL. This data is published to Kafka topics, then vectorized and used with artificial intelligence to enhance the overall process. It's like an old-fashioned approach. The best way is to redesign it with products such as Kafka. Overall, I rate the solution an eight out of ten.

Quotes from Members

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

Pros

"We mostly use the solution's message queues and event-driven architecture."
"I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and tools."
"Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"The client APIs are the most valuable feature."
"The benefit is escaping email communication. Sometimes people ignore emails or put them into spam, but with Confluence, everyone sees the same text at the same time."
"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."
"Their tech support is amazing; they are very good, both on and off-site."
"It is a stable solution."
"Cloud Pak for Integration is definitely scalable. That is the most important criteria."
"The most valuable aspect of the Cloud Pak, in general, is the flexibility that you have to use the product."
"Redirection is a key feature. It helps in managing multiple microservices by centralizing control and access."
"The most preferable aspect would be the elimination of the command, which was a significant improvement. In the past, it was a challenge, but now we can proceed smoothly with the implementation of our policies and everything is managed through JCP. It's still among the positive aspects, and it's a valuable feature."
 

Cons

"One area we've identified that could be improved is the governance and access control to the Kafka topics. We've found some limitations, like a threshold of 10,000 rules per cluster, that make it challenging to manage access at scale if we have many different data sources."
"The product should integrate tools for incorporating diagrams like Lucidchart. It also needs to improve its formatting features. We also faced issues while granting permissions."
"They should remove Zookeeper because of security issues."
"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"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."
"It could have more integration with different platforms."
"Confluence could improve the server version of the solution. However, most companies are going to the cloud."
"The initial setup is not easy."
"Enterprise bots are needed to balance products like Kafka and Confluent."
"Its queuing and messaging features need improvement."
"The pricing can be improved."
"Setting up Cloud Pak for Integration is relatively complex. It's not as easy because it has not yet been fully integrated. You still have some products that are still not containerized, so you still have to run them on a dedicated VM."
 

Pricing and Cost Advice

"The solution is cheaper than other products."
"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."
"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."
"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."
"Confluent is highly priced."
"It comes with a high cost."
"Confluent is an expensive solution as we went for a three contract and it was very costly for us."
"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."
"The solution's pricing model is very flexible."
"It is an expensive solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Computer Software Company
16%
Manufacturing Company
6%
Insurance Company
5%
Financial Services Firm
21%
Computer Software Company
10%
Insurance Company
9%
Government
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Confluent?
I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and to...
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?
I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team. The lack of easy access to the Confluent support team is also a...
What do you like most about IBM Cloud Pak for Integration?
The most preferable aspect would be the elimination of the command, which was a significant improvement. In the past, it was a challenge, but now we can proceed smoothly with the implementation of ...
What needs improvement with IBM Cloud Pak for Integration?
Enterprise bots are needed to balance products like Kafka and Confluent.
What is your primary use case for IBM Cloud Pak for Integration?
It manages APIs and integrates microservices at the enterprise level. It offers a range of capabilities for handling APIs, microservices, and various integration needs. The platform supports thousa...
 

Overview

 

Sample Customers

ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost
CVS Health Corporation
Find out what your peers are saying about Confluent vs. IBM Cloud Pak for Integration and other solutions. Updated: June 2025.
859,129 professionals have used our research since 2012.