Confluent vs IBM Cloud Pak for Integration comparison

Confluent and IBM are both solutions in the Cloud Data Integration category. Additionally, 95% of Confluent users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Confluent

Read 25 Confluent reviews

6,170 Views
3,579 Comparison Views

95% willing to recommend

IBM Cloud Pak for Integration

Read 5 IBM Cloud Pak for Integration reviews

2,500 Views
900 Comparison Views

100% willing to recommend

Confluent

IBM Cloud Pak for Integration

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Executive Summary

We performed a comparison between Confluent and IBM Cloud Pak for Integration based on real PeerSpot user reviews.

Find out what your peers are saying about Amazon Web Services (AWS), Informatica, Palantir and others in Cloud Data Integration.

To learn more, read our detailed Cloud Data Integration Report (Updated: August 2026).

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Cloud Data Integration

August 2026

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Helped 909,725 peers since 2012

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

6.3

Number of Reviews

Ranking in other categories

Streaming Analytics (7th)

IBM Cloud Pak for Integration

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

API Management (29th), Cloud Data Integration (20th)

Featured Reviews

PavanManepalli

AVP - Sr Middleware Messaging Integration Engineer at Wells Fargo

Has supported streaming use cases across data centers and simplifies fraud analytics with SQL-based processing

I recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about Confluent charging high fees while not offering features that match those of other tools. They need to improve in that direction by not only reducing costs but also providing better solutions for the problems customers face to avoid frustrations, whether through future enhancement requests or ensuring product stability. The cost should be worked on, and they should provide better solutions for customers. Solutions should focus on hierarchical topics; if a customer has different types of data and sources, they should be able to send them to the same place for analytics. Currently, Confluent requires everything to send to the same topic, which becomes very large and makes running analytics difficult. The hierarchy of topics should be improved. This part is available in MQ and other products such as Solace, but it is missing in Confluent, leading many in capital markets and trading to switch to Solace. In terms of stability, it is not the stability itself that needs improvement but rather the delivery semantics. Other products offer exactly-once delivery out of the box, whereas Confluent states it will offer this but lacks the knobs or levers for tuning configurations effectively. Confluent has hundreds of configurations that application teams must understand, which creates a gap. Users are often unaware of what values to set for better performance or to achieve exactly-once semantics, making it difficult to navigate through them. Delivery semantics also need to be worked on.

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Igor Khalitov

Owner/Full Stack Software Engineer at Maraphonic, Inc.

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.

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Quotes from Members

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

Pros

"Confluence's greatest asset is its user-friendly interface, coupled with its remarkable ability to seamlessly integrate with a vast range of other solutions."

"To date, we have seen improvements in performance and scalability, so we recommend this solution."

"Confluent facilitates the messaging tasks with Kafka, streamlining our processes effectively."

"Their tech support is amazing; they are very good, both on and off-site."

"A person with a good IT background and HTML will not have any trouble with Confluent."

"One of the best features of Confluent is that it's very easy to search and have a live status with Jira."

"We primarily use Confluent for service desk and task management, and it is also good for knowledge base management."

"Some of the best features are that it's very quick to set up, very easy to have a centralized area that gives us a history of changes, and the ability to give feedback on any information placed onto the pages."

More Confluent pros

"Cloud Pak for Integration is definitely scalable. That is the most important criteria."

"Redirection is a key feature. It helps in managing multiple microservices by centralizing control and access."

"It is a stable solution."

"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."

"The most valuable aspect of the Cloud Pak, in general, is the flexibility that you have to use the product."

"In general, the solution works very, very well."

Cons

"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."

"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."

"In Confluent, there could be a few more VPN options."

"It could have more themes. They should also have more reporting-oriented plugins as well. It would be great to have free custom reports that can be dispatched directly from Jira."

"It could be more user-friendly and centralized. A way to reduce redundancy would be helpful."

"Confluent has a good monitoring tool, but it's not customizable."

"Recently, there has been a lot of buzz about Confluent charging high fees while not offering features that match those of other tools."

"The solution could have an extra plugin or upgrading feature. In addition, it could have more integration with different platforms and be more compatible."

More Confluent cons

"Enterprise bots are needed to balance products like Kafka and Confluent."

"What needs to be improved is the restriction that they have on the product."

"Its queuing and messaging features need improvement."

"The initial setup is not easy."

"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 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."

"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."

"The solution is cheaper than other products."

"Confluent is an expensive solution as we went for a three contract and it was very costly for us."

"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."

"You have to pay additional for one or two features."

"Confluent has a yearly license, which is a bit high because it's on a per-user basis."

More Confluent pricing and cost advice

"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

15%

Retailer

12%

Computer Software Company

Manufacturing Company

Financial Services Firm

13%

Manufacturing Company

12%

Construction Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	4
Large Enterprise	17

No data available

Questions from the Community

What is your experience regarding pricing and costs for Confluent?

They charge a lot for scaling, which makes it expensive.

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What needs improvement with Confluent?

See all answers

What is your primary use case for Confluent?

The main use cases for Confluent are log aggregation and streaming. I'm familiar with Confluent stream processing with KSQL. KSQL helps in terms of data analytics strategies because if we are the d...

See all answers

What needs improvement with IBM Cloud Pak for Integration?

Enterprise bots are needed to balance products like Kafka and Confluent.

See all answers

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...

See all answers

What advice do you have for others considering IBM Cloud Pak for Integration?

See all answers

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Compared 12% of the time

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Compared 10% of the time

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Compared 9% of the time

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Compared 9% of the time

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Compared 7% of the time

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Product Reports

Buyer's Guide

Confluent

August 2026

Download Confluent product report

Buyer's Guide

API Management

August 2026

Download IBM Cloud Pak for Integration product report

Overview

Confluent offers scalable, open-source flexibility and seamless data replication, supported by strong cloud integration. Key features like Kafka Connect and real-time processing make it valuable for data streaming projects while ensuring high availability with a Multi-Region Cluster.

Confluent is a robust data streaming platform that enables efficient management and integration of real-time data pipelines. Its message-driven architecture and fault tolerance provide reliability, while a user-friendly dashboard and connectors support diverse data sources. Cloud integration reduces costs, and extensive documentation, plugins, and monitoring capabilities enhance collaboration and revision management. Despite some areas needing improvement, including security in the SaaS version and integration flexibility, Confluent remains a staple in industries requiring vast data processing and task automation.

What are Confluent's key features?

Scalability: Handles large volumes of data, ensuring continuous performance.
Kafka Connect: Enables seamless data integration across multiple systems.
Real-time Processing: Facilitates instant data insights for rapid decision-making.
Multi-Region Cluster: Maintains data availability across different geographical locations.
Cloud Integration: Reduces operational costs and enhances deployment flexibility.
User Dashboard: Simplifies management with an intuitive interface.

What benefits and ROI should users consider in reviews?

Cost-Efficiency: Improved processes reduce operational expenses.
Data Reliability: Ensures consistent and accurate data handling.
Increased Collaboration: Boosts team efficiency with comprehensive documentation and management tools.
Scalability: Supports business growth without compromising performance.
Integration Flexibility: Seamlessly connects with diverse data sources and systems.

Confluent is commonly implemented in finance, insurance, and software industries for applications like fraud detection, ETL tasks, and enterprise communication. It supports real-time data processing, project management, and task automation, often integrating with project management tools like Jira, providing valuable solutions for business processes.

Confluent

IBM Cloud Pak for Integration offers multi-cloud management and automation, focusing on connecting core systems for seamless integration using advanced technologies and efficient API management.

IBM Cloud Pak for Integration provides flexibility, automation, and accounting tools on the OpenShift Container Platform, easing license and management. Among its notable features are effective streaming capabilities, simplified policy implementation via JCP, and enhanced control with redirection, particularly beneficial for microservices management. Its stability and practical container management are major advantages. However, limitations include exclusive IBM product deployment over OpenShift and complex initial setup. Users seek better pricing, enhanced streaming features, improved queuing and messaging, and integration with monitoring tools. Enhanced enterprise bots are needed for balance with Kafka and Confluent.

What are IBM Cloud Pak for Integration's key features?

Flexibility: Supports multi-cloud management and automation for seamless integration.
Streaming: Effective streaming feature for data processing and policy implementation.
Redirection: Enhances control and access for microservices management.
OpenShift Platform: Simplifies licensing and management with container technology.

What benefits should users look for in reviews?

Efficiency: Simplified policy implementation and automation reduce operational challenges.
Control: Enhanced management of microservices and APIs for streamlined operations.
Stability: Robust container management for consistent performance.
Integration: Supports integration with multiple technologies like Kafka and DataPower.

Implemented across industries like travel and banking, IBM Cloud Pak for Integration aids in connecting core systems and enables effective automation and API management. It supports data conversion, format alterations, and comprehensive management of numerous APIs, providing deployment options based on specific needs.

IBM

Sample Customers

ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost

CVS Health Corporation

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Cloud Data Integration

August 2026

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