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IBM Cloud Pak for Data vs Palantir Foundry comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 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 Data
Ranking in Data Integration
23rd
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
14
Ranking in other categories
Data Virtualization (3rd)
Palantir Foundry
Ranking in Data Integration
12th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
17
Ranking in other categories
IT Operations Analytics (10th), Supply Chain Analytics (1st), Cloud Data Integration (11th), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of January 2026, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.3%, down from 1.6% compared to the previous year. The mindshare of Palantir Foundry is 2.3%, down from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Palantir Foundry2.3%
IBM Cloud Pak for Data1.3%
Other96.4%
Data Integration
 

Featured Reviews

Michelle Leslie - PeerSpot reviewer
Data asset management engineer at a tech services company with 1-10 employees
Starts strong with data management capabilities but needs a demo database
What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data management, and more often than not, people understand one thing really well. They may understand DataStage and how to move data around, but they do not see the impact of moving data incorrectly. They also do not see the impact of everyone understanding a piece of data in the same way. I would love Cloud Pak to come with a demo database that illustrates the different components of data management in a logical way, so I can see the whole picture instead of just the area I'm specializing in. It would be great if Cloud Pak, from a data modeling point of view, allowed us to import our PDMs, for example. It would be ideal to import and create business terms in Cloud Pak. The PEA would be great to create the technical data. The association between the business and the technical metadata could then be automated by pulling it through from your ACE models. The data modeling component is available in Cloud Pak. Additionally, when it comes to Cloud Pak, even though it has the NextGen DataStage built into it, there is Cloud Pak for data integration as well. Currently, I do not think we have a full enough understanding of how CP4D and CP4I can enhance each other.
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

"Its data preparation capabilities are highly valuable."
"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."
"IBM Watson Catalog and data pipelines are the most valuable features of the solution."
"IBM Cognos is very stable and has been around for many years, with many users familiar with it, making it a reliable solution for our institution."
"It is a scalable solution, and we have had no issues with its scalability in our company. I rate the solution's scalability a nine out of ten."
"What I found most helpful in IBM Cloud Pak for Data is containerization, which means it's easy to shift and leave in terms of moving to other clouds. That's an advantage of IBM Cloud Pak for Data."
"I love the way that I can start at a very basic level with my data management journey by capturing my policies, justifying my data, and putting them into different categories to say this is data relating to individuals, for example, or data relating to geography."
"Cloud Pak's most valuable features are IBM MQ, IBM App Connect, IBM API Connect, and ISPF."
"I like the data onboarding to Palantir Foundry and ETL creation."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"Great features available in one tool."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"The solution offers very good end-to-end capabilities."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"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."
"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."
 

Cons

"The technical support could be a little better."
"The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem."
"The interface could improve because sometimes it becomes slow. Sometimes there is a delay between clicks when using the software, which can make the development process slow. It can take a few seconds to complete one action, and then a few more seconds to do the next one."
"Cloud Pak would be improved with integration with cloud service providers like Cloudera."
"The solution's user experience is an area that has room for improvement."
"The product must improve its performance."
"One challenge I'm facing with IBM Cloud Pak for Data is native features have been decommissioned, such as XML input and output. Too many changes have been made, and my company has around one hundred thousand mappings, so my team has been putting more effort into alternative ways to do things. Another area for improvement in IBM Cloud Pak for Data is that it's more complicated to shift from on-premise to the cloud. Other vendors provide secure agents that easily connect with your existing setup. Still, with IBM Cloud Pak for Data, you have to perform connection migration steps, upgrade to the latest version, etc., which makes it more complicated, especially as my company has XML-based mappings. Still, the XML input and output capabilities of IBM Cloud Pak for Data have been discontinued, so I'd like IBM to bring that back."
"The solution could have more connectors."
"If you want to create new models on specific data sets, computing that is quite costly."
"The workflow could be improved."
"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."
"Cost of this solution is quite high."
"The startup pricing is high, causing concern despite being cost-effective in terms of total cost of ownership."
"The solution could use more online documentation for new users."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
 

Pricing and Cost Advice

"I think that this product is too expensive for smaller companies."
"The solution's pricing is competitive with that of other vendors."
"Cloud Pak's cost is a little high."
"IBM Cloud Pak for Data is expensive. If we include the training time and the machine learning, it's expensive. The cost of the execution is more reasonable."
"For the licensing of the solution, there is a yearly payment that needs to be made. Also, since it is expensive, cost-wise, I rate the solution an eight or nine out of ten."
"The solution is expensive."
"It's quite expensive."
"I don't have the exact licensing cost for IBM Cloud Pak for Data, as my company is still finalizing requirements, including monthly, yearly, and three-year licensing fees. Still, on a scale of one to five, I'd rate it a three because, compared to other vendors, it's more complicated."
"Palantir Foundry is an expensive solution."
"Palantir Foundry has different pricing models that can be negotiated."
"It's expensive."
"The solution’s pricing is high."
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Top Industries

By visitors reading reviews
Financial Services Firm
26%
Manufacturing Company
9%
Computer Software Company
9%
University
5%
Manufacturing Company
13%
Financial Services Firm
10%
Government
8%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business7
Large Enterprise10
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise5
Large Enterprise8
 

Questions from the Community

What is your experience regarding pricing and costs for IBM Cloud Pak for Data?
The setup cost is very expensive. The cost depends on the pieces of the solution I'm using, how much data I have, and whether it's on the cloud or on-prem.
What needs improvement with IBM Cloud Pak for Data?
What I would love to see is an end-to-end, almost a training demo database of some sort, where one of the biggest problems with data management is demonstrated. There are so many components to data...
What is your primary use case for IBM Cloud Pak for Data?
My primary use case for Cloud Pak is that I am the reference Data steward for the Africa regions in the banks where I work. My main objective is to capture the reference data in Caltech or Data and...
What do you like most about Palantir Foundry?
Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration.
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...
 

Also Known As

Cloud Pak for Data
No data available
 

Overview

 

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival
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 Data vs. Palantir Foundry and other solutions. Updated: December 2025.
879,443 professionals have used our research since 2012.