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CloverETL 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

CloverETL
Average Rating
7.0
Reviews Sentiment
6.8
Number of Reviews
2
Ranking in other categories
Data Integration (60th), Data Visualization (40th)
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

it_user856614 - PeerSpot reviewer
Very easy to schedule jobs and monitor them, however we run out heap space even with a high allocation
Flexibility: We can bring in data from multiple sources, e.g., databases, text files, JSON, email, XML, etc. This has been very helpful Connectivity to various data sources: The ability to extract data from different data sources gives greater flexibility. Server features for scheduler: It is…
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

"Connectivity to various data sources: The ability to extract data from different data sources gives greater flexibility."
"Key features include wealth of pre-defined components; all components are customizable; descriptive logging, especially for error messages."
"Server features for scheduler: It is very easy to schedule jobs and monitor them. The interface is easy to use."
"No dependence on native language and ease of use.​​"
"Redirection is a key feature. It helps in managing multiple microservices by centralizing control and access."
"The most valuable aspect of the Cloud Pak, in general, is the flexibility that you have to use the product."
"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."
"Cloud Pak for Integration is definitely scalable. That is the most important criteria."
 

Cons

"Needs: easier automated failure recovery; more, and more intuitive auto-generated/filled-in code for components; easier/more automated sync between CloverETL Designer and CloverETL Server."
"Its documentation could be improved.​"
"​Resource management: We typically run out of heap space, and even the allocation of high heap space does not seem to be enough.​"
"Enterprise bots are needed to balance products like Kafka and Confluent."
"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."
"Its queuing and messaging features need improvement."
"The initial setup is not easy."
"The pricing can be improved."
 

Pricing and Cost Advice

Information not available
"The solution's pricing model is very flexible."
"It is an expensive solution."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
21%
Computer Software Company
10%
Government
9%
Insurance Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

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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

IBM, Oracle, MuleSoft, GoodData, Thomson Reuters, salesforce.com, Comcast, Active Network, SHOP.CA
CVS Health Corporation
Find out what your peers are saying about CloverETL vs. IBM Cloud Pak for Integration and other solutions. Updated: July 2025.
861,524 professionals have used our research since 2012.