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IBM Cloud Pak for Integration vs Striim 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

IBM Cloud Pak for Integration
Ranking in Cloud Data Integration
20th
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
5
Ranking in other categories
API Management (29th)
Striim
Ranking in Cloud Data Integration
27th
Average Rating
8.0
Reviews Sentiment
6.2
Number of Reviews
2
Ranking in other categories
Data Integration (47th), Streaming Analytics (23rd)
 

Mindshare comparison

As of August 2026, in the Cloud Data Integration category, the mindshare of IBM Cloud Pak for Integration is 1.2%, down from 2.0% compared to the previous year. The mindshare of Striim is 1.1%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
IBM Cloud Pak for Integration1.2%
Striim1.1%
Other97.7%
Cloud Data Integration
 

Featured Reviews

Igor Khalitov - PeerSpot reviewer
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.
RV
Data Engineer
Real-time data capture has accelerated releases and now improves trust in our data warehouse
The checkpoints would help me to figure out where the problem was if there's any lag, but I had to do a lot of manual work to figure out where the lag is. Striim would not intuitively tell me the culprit table or database behind the lag. I believe that is an improvement Striim could definitely do. Passwords were an issue. Property variables were not supported for passwords, meaning I had to make sure the password is manually populated. I believe if Striim could read from AWS secrets or its own secret mechanism to store the password, that would really save a lot of time so that I don't have to keep updating the password whenever there is any change. The user experience of triggering alerts if there's any lag which Striim identified, which is outside normal processing time, could intrinsically be done by Striim. I believe that was lacking. I would wait for Striim to tell me, instead of me going and validating whether Striim is lagging behind. If Striim could itself tell me that it's seeing a lot more volume than expected, that would really make me give it a higher number.

Quotes from Members

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

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."
"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."
"It is a stable solution."
"In general, the solution works very, very well."
"We were confidently in a situation to call Snowflake as a single source of truth, and I believe with Striim, we were able to do that because without Striim, the SLA would be much higher, and there would not have been much confidence in Snowflake."
"Striim is capable of absorbing a large number of transactions, and the difference between the two databases is always less than a second, which demonstrates efficiency and highlights the variety of sources and targets I have used."
 

Cons

"The initial setup is not easy."
"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."
"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."
"The pricing can be improved."
"Its queuing and messaging features need improvement."
"I think Striim could be improved with better pricing and enhanced documentation."
"The user experience of triggering alerts if there's any lag which Striim identified, which is not normal, could intrinsically be done by Striim."
 

Pricing and Cost Advice

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

By visitors reading reviews
Financial Services Firm
13%
Manufacturing Company
11%
Construction Company
9%
Government
8%
Construction Company
16%
Healthcare Company
13%
Retailer
12%
Financial Services Firm
10%
 

Company Size

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

Questions from the Community

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...
What advice do you have for others considering IBM Cloud Pak for Integration?
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. Addition...
What is your experience regarding pricing and costs for Striim?
My experience with the pricing, implementation cost, and licensing of Striim is that it is somewhat expensive.
What needs improvement with Striim?
I think Striim could be improved with better pricing and enhanced documentation.
What is your primary use case for Striim?
I use Striim to perform change data capture from relational databases to non-relational databases in my organization. I implement CDC with Striim by transferring data from Oracle Database to MongoD...
 

Also Known As

No data available
Striim Platform
 

Overview

 

Sample Customers

CVS Health Corporation
Sky, UPS, MACY'S, EMAAR, HSBC
Find out what your peers are saying about IBM Cloud Pak for Integration vs. Striim and other solutions. Updated: August 2026.
909,153 professionals have used our research since 2012.