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IBM Cloud Pak for Integration vs Palantir Foundry comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 3, 2024

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
16th
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
5
Ranking in other categories
API Management (28th)
Palantir Foundry
Ranking in Cloud Data Integration
11th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
17
Ranking in other categories
Data Integration (12th), IT Operations Analytics (10th), Supply Chain Analytics (1st), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of January 2026, in the Cloud Data Integration category, the mindshare of IBM Cloud Pak for Integration is 1.7%, up from 1.7% compared to the previous year. The mindshare of Palantir Foundry is 4.9%, up from 3.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Integration Market Share Distribution
ProductMarket Share (%)
Palantir Foundry4.9%
IBM Cloud Pak for Integration1.7%
Other93.4%
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.
SR
Architect at L&T Technology Services
Finds security and customization features impressive, although cost concerns persist
My experience with Palantir Foundry and Azure has been good. Palantir Foundry is costly, but Azure is open, which allows for easier experimentation. Being a closed product, Palantir Foundry is difficult to practice offline unless we have an enterprise edition. However, it is very secure compared to other platforms. Palantir Foundry's best features include security, built-in features, low-code, no-code platform, and ease of use. The collaborative workspaces within Palantir Foundry contribute to team efficiency and project outcomes through seamless operation. The ease of customization is particularly notable. I have worked with the data lineage feature in Palantir Foundry, which comes by default. We simply need to tick the checkbox and make necessary configuration changes within the system itself. We do not need to procure another lineage platform as Palantir Foundry has its own built-in features for data lineage, data governance, and data security. The lineage feature helps enhance our data management practices by allowing us to understand the origin of data, track all activities happening on the data, identify users and consumers, and monitor how it flows across the system. This makes it easier to generate reports based on the lineage database. The predictive analytics capability within Palantir Foundry impacts financial forecasting strategies through its AIP functionality, which includes numerous pre-built models, LLMs, and data science application libraries. Using the AIP library within Palantir Foundry helps us develop quick resolutions for predictive models and analytics.

Quotes from Members

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

Pros

"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."
"Cloud Pak for Integration is definitely scalable. That is the most important criteria."
"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."
"It is a stable solution."
"The virtualization tool is useful."
"Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration."
"The security is also excellent. It's highly granular, so the admins have a high degree of control, and there are many levels of security. That worked well. You won't have an EDC unless you put everything onto the platform because it is its own isolated thing."
"The data lineage is great."
"Great features available in one tool."
"It's scalable."
"The ease of use is my favorite feature. We're able to build different models and projects or combine different projects to build one use case."
"I rate Palantir Foundry a ten out of ten."
 

Cons

"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."
"Enterprise bots are needed to balance products like Kafka and Confluent."
"The initial setup is not easy."
"Its queuing and messaging features need improvement."
"Difficult to receive data from external sources."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"The workflow could be improved."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"The major hindrance with Palantir Foundry is that being a very closed product, the cost optimization and costing are not exposed to the end users."
"They do not have a data center in Europe, and we have lots of personally identifiable information in our dataset that needs to be hosted by a third-party data center like Amazon or Microsoft Azure."
"The solution's visualization and analysis could be improved."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
 

Pricing and Cost Advice

"The solution's pricing model is very flexible."
"It is an expensive solution."
"Palantir Foundry is an expensive solution."
"It's expensive."
"The solution’s pricing is high."
"Palantir Foundry has different pricing models that can be negotiated."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Government
13%
Insurance Company
8%
Computer Software Company
8%
Manufacturing Company
14%
Financial Services Firm
10%
Government
8%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise5
Large Enterprise8
 

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 needs improvement with Palantir Foundry?
Apart from the pricing and offline availability issues, improvements are needed in Palantir Foundry's costing factor. Cost-wise, it is not open for everybody, and they are not exposing anything out...
What is your primary use case for Palantir Foundry?
One of the leading European manufacturing plants uses Palantir Foundry for manufacturing interior parts of various car brands such as Honda, Hyundai, Ford, Mercedes-Benz, and BMW. This involves hig...
What advice do you have for others considering Palantir Foundry?
Palantir Foundry is an excellent product for data engineering. On a scale of one to 10, I would rate Palantir Foundry a 9.
 

Overview

 

Sample Customers

CVS Health Corporation
Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Find out what your peers are saying about IBM Cloud Pak for Integration vs. Palantir Foundry and other solutions. Updated: December 2025.
881,114 professionals have used our research since 2012.