IBM Cloud Pak for Data vs Palantir Foundry comparison

IBM and Palantir are both solutions in the Data Integration category. IBM is ranked #19 with an average rating of 8.4, while Palantir is ranked #13 with an average rating of 8.0. IBM holds a 1.2% mindshare in DI, compared to Palantir’s 2.1% mindshare. Additionally, 91% of IBM users are willing to recommend the solution, compared to 88% of Palantir users who would recommend it.

IBM Cloud Pak for Data

Read 21 IBM Cloud Pak for Data reviews

3,029 Views
2,787 Comparison Views

91% willing to recommend

Palantir Foundry

Read 18 Palantir Foundry reviews

11,675 Views
4,904 Comparison Views

88% willing to recommend

IBM Cloud Pak for Data

Palantir Foundry

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 19, 2024

Palantir Foundry and IBM Cloud Pak for Data are leading platforms in data integration and analytics, with Foundry often leading in advanced data management capabilities and Cloud Pak for Data excelling in AI-driven analytics thanks to comprehensive features.

Features: Palantir Foundry offers robust real-time data insights with advanced data integration, dynamic analysis, and scalability tailored for intricate data environments. IBM Cloud Pak for Data stands out with AI technologies integration, broad machine learning ecosystem, and data virtualization capabilities that enhance analytics efficiency.

Room for Improvement: Palantir Foundry's steep pricing and complexity in initial setup are potential drawbacks that some businesses face. Additionally, the platform's focus on advanced users may not cater well to less technical teams. IBM Cloud Pak for Data could improve in simplifying deployment processes and optimizing cloud transitions. Enhancing usability for non-AI-centric tasks could also be beneficial.

Ease of Deployment and Customer Service: Palantir Foundry is noted for intuitive deployment and comprehensive support, facilitating seamless transitions for businesses. In contrast, IBM Cloud Pak for Data offers flexibility in hybrid cloud environments, with strong support services but may have a steeper learning curve during deployment.

Pricing and ROI: Palantir Foundry incurs higher costs but delivers strong ROI for complex needs, justifying the expense with its potent capabilities. IBM Cloud Pak for Data provides a more cost-effective setup with substantial ROI for businesses emphasizing AI, making it financially appealing for a broader audience.

To learn more, read our detailed IBM Cloud Pak for Data vs. Palantir Foundry Report (Updated: April 2026).

Buyer's Guide

IBM Cloud Pak for Data vs. Palantir Foundry

April 2026

Download the complete report

Helped 895,272 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

IBM Cloud Pak for Data

Ranking in Data Integration

19th

Average Rating

8.2

Reviews Sentiment

6.2

Number of Reviews

Ranking in other categories

Data Virtualization (3rd)

Palantir Foundry

Ranking in Data Integration

13th

Average Rating

7.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

IT Operations Analytics (8th), Supply Chain Analytics (1st), Cloud Data Integration (10th), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)

Mindshare comparison

As of May 2026, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.2%, down from 1.8% compared to the previous year. The mindshare of Palantir Foundry is 2.1%, down from 2.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Palantir Foundry	2.1%
IBM Cloud Pak for Data	1.2%
Other	96.7%

Data Integration

Featured Reviews

Raman Shihan

Sr. Data Engineer at LTM

Unified data workflows have transformed how I manage sensitive analytics and end-to-end AI

One of the things that IBM Cloud Pak for Data does well is the data privacy and security that it offers. Since most of my data is very sensitive, IBM privacy framework helps me secure it very conveniently. In my experience, some of the best features that I encounter in IBM Cloud Pak for Data are the AI and Watson Assistant, which is very good. The analytics dashboard featuring all the recent history is very good with IBM. Searching for data through the unified search option is super cool. Among those features, the artificial intelligence that solves everything automatically stands out as most valuable in my day-to-day work, saving a lot of time. I can also store my data in many clouds with all the desired data. The customer service system is excellent and always willing to help. I would also add that the project analytics dashboard, ability to manage data across different cloud platforms, and end-to-end AI lifecycle are very great. IBM Cloud Pak for Data has positively impacted my organization by helping me see some return on investments. I have the ability to access all my data much quicker through the unified search option. It has also improved data security and governance in my organization very well. I've seen a 30% increase in productivity through the introduction of AI with IBM Cloud Pak for Data, which has really simplified a lot of operations that were manually tackled.

Read full review

Sai Arun Bandhakavi

Associate Vice President at a insurance company with 10,001+ employees

Unified data workflows have empowered collaborative analytics and streamlined AI development

Regarding points for improvement for Palantir Foundry, I see that they are improving day by day. In the last one to two years, I have seen many improvements compared to the two years that I have worked on Palantir Foundry. There are many things that come up, but a few things are not intuitive enough. Now that we are in this AI phase, Palantir Foundry has created some wrappers around the models, allowing us to create using a no-code application, chatbots, and LLM functions. The problem is that interaction with outside applications can be difficult with the current setup that Palantir Foundry has. There are ways to do that, but it is not that intuitive, which is what I feel.

Read full review

Quotes from Members

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

Pros

"Cloud Pak is a very, very, very good system."

"The most valuable features of IBM Cloud Pak for Data are the Watson Studio, where we can initiate more groups and write code. Additionally, Watson Machine Learning is available with many other services, such as APIs which you can plug the machine learning models."

"One of Cloud Pak's best features is the Watson Knowledge Catalog, which helps you implement data governance."

"IBM Cloud Pak for Data is a very useful tool because it has the entire gamut of tools, starting from collecting the data from various sources using direct integration or through data virtualization and then organizing it into catalogs and applying their organization's policies or if they have other enforcement policies on top of that."

"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."

"The most valuable feature of IBM Cloud Pak for Data is the Modeler flows. The ability to develop models using a graphical approach and the capability to connect to various sources, as well as the data virtualization capabilities, allow me to easily access and utilize data that is dispersed across different sources."

"The most valuable features are data virtualization and reporting."

More IBM Cloud Pak for Data pros

"Great features available in one tool."

"The virtualization tool is useful."

"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."

"Based on my huge experience with Palantir Foundry, I find that starting from the data connection to the end user application, there is a tool for everyone."

"The solution offers very good end-to-end capabilities."

"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."

"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."

"I rate Palantir Foundry a ten out of ten."

More Palantir Foundry pros

Cons

"The initial setup was a little complex. It is not that user-friendly, and it needs quite a bit of expertise to install, the installation between various different vendors is even more difficult, such as deploying it on the IBM Cloud is relatively easier than having it installed in Amazon AWS or Microsoft Azure, or similar cloud service."

"The two main challenges that I face are setup complexity and customer support responsiveness."

"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."

"One thing that bugs me is how much infrastructure Cloud Pak requires for the initial deployment. It doesn't allow you to start small. The smallest permitted deployment is too big. It's a huge problem that prevents us from implementing the solution in many scenarios."

"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."

"There is a solution that is part of IBM Cloud Pak for Data called Watson OpenScale. It is used to monitor the deployed models for the quality and fairness of the results. This is one area that needs a lot of improvement."

"The tool depends on the control plane, an OpenShift container platform utilized as an orchestration layer...So, we have communicated this issue to IBM and asked if it is feasible to adapt the solution to work on a Kubernetes platform that we support."

More IBM Cloud Pak for Data cons

"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."

"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."

"It requires a lot of manual work and is very time-consuming to get to a functional point."

"If you want to create new models on specific data sets, computing that is quite costly."

"The problem is that interaction with outside applications can be difficult with the current setup that Palantir Foundry has."

"I rate Palantir Foundry five out of 10. I'm ambivalent."

"The data lineage was challenging. It's hard to track data from the sources as it moves through stages. Informatica EDC can easily capture and report it because it talks to the metadata. This is generated across those various staging points."

More Palantir Foundry cons

Pricing and Cost Advice

"It's quite expensive."

"The solution is expensive."

"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."

"I think that this product is too expensive for smaller companies."

"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."

"Cloud Pak's cost is a little high."

"The solution's pricing is competitive with that of other vendors."

"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 has different pricing models that can be negotiated."

"It's expensive."

"Palantir Foundry is an expensive solution."

"The solution’s pricing is high."

See which vendors are best for you

Use our free recommendation engine to learn which Data Integration solutions are best for your needs.

See recommendations

895,272 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

20%

Manufacturing Company

10%

Computer Software Company

University

Manufacturing Company

13%

Financial Services Firm

Government

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	9
Large Enterprise	18

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	5
Large Enterprise	13

Questions from the Community

What is your experience regarding pricing and costs for IBM Cloud Pak for Data?

Regarding the price, I know IBM is traditionally relatively expensive in the Hungarian market, but we work together with the local IBM sales team, and on a project basis they manage to negotiate th...

See all answers

What needs improvement with IBM Cloud Pak for Data?

I see room for improvement in IBM Cloud Pak for Data, as it lacked the lake house. However, IBM issued the new product which is Watsonx.data. This is a new product for IBM and it provides all the m...

See all answers

What is your primary use case for IBM Cloud Pak for Data?

I believe IBM Cloud Pak for Data is suitable for mid-size to bigger companies. It is not tailored for smaller customers. My customers use IBM DataStage for ETL processes. One client has implemented...

See all answers

What needs improvement with Palantir Foundry?

See all answers

What is your primary use case for Palantir Foundry?

There are several use cases that we are working on with Palantir Foundry. The first thing is for data model creation for all our data engineering pipelines. That is one use case. Palantir Foundry a...

See all answers

What advice do you have for others considering Palantir Foundry?

The visualization part in Palantir Foundry works for me at least if I want to see how the data is structured and for an initial analysis, but I would say it is not as matured as Power BI or Tableau...

See all answers

Comparisons

IBM InfoSphere DataStage vs IBM Cloud Pak for Data

Compared 16% of the time

Import.io vs IBM Cloud Pak for Data

Compared 6% of the time

Denodo vs IBM Cloud Pak for Data

Compared 6% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs IBM Cloud Pak for Data

Compared 6% of the time

Fivetran vs IBM Cloud Pak for Data

Compared 3% of the time

More IBM Cloud Pak for Data Competitors

Cognizant AI & Analytics vs Palantir Foundry

Compared 6% of the time

Confluent vs Palantir Foundry

Compared 4% of the time

Palantir Gotham vs Palantir Foundry

Compared 3% of the time

MuleSoft Anypoint Platform vs Palantir Foundry

Compared 3% of the time

Databricks vs Palantir Foundry

Compared 3% of the time

More Palantir Foundry Competitors

Product Reports

Buyer's Guide

IBM Cloud Pak for Data

May 2026

Download IBM Cloud Pak for Data product report

Buyer's Guide

Palantir Foundry

May 2026

Download Palantir Foundry product report

Also Known As

Cloud Pak for Data

No data available

Overview

IBM Cloud Pak for Data is a comprehensive platform integrating data management, AI, and machine learning capabilities tailored for hybrid environments. It's renowned for enhancing productivity through efficient data analytics and management.

This platform offers data virtualization, robust analytics, and AI-driven processes. Its integration capabilities, including IBM MQ and App Connect, facilitate seamless data connections. Users benefit from containerization, data governance, and compatibility with hybrid systems, improving decision-making and management productivity. However, the requirement of extensive infrastructure and performance challenges can impact scalability for small businesses.

What are the key features of IBM Cloud Pak for Data?

Watson Knowledge Catalog: Organizes data for accessibility and insight extraction.
Data Virtualization: Provides a unified data view across sources without copying data.
Robust Analytics: Offers advanced analytics tools for data-driven decision-making.
Integration Capabilities: Includes IBM MQ and App Connect for seamless data integration.
AI and Machine Learning: Supports AI-driven insights and learning models.

What benefits or ROI should users expect?

Enhanced Productivity: Streamlines data management processes, enhancing efficiency.
Better Business Decisions: Utilizes analytics for informed strategic choices.
Improved Data Governance: Ensures compliance and quality in data handling.
Collaboration: Encourages teamwork with a comprehensive platform supporting analytics.

In the financial and banking sectors, IBM Cloud Pak for Data is utilized for data management tasks like spend analytics and contract leakage analysis. It's used for data integration, machine learning, and AI-driven analytics to transform data into valuable insights in industries such as FinTech and consultancy.

IBM

Palantir Foundry offers intuitive data management and application development, prioritizing accessibility through low-code/no-code tools, enabling users to integrate, analyze, and collaborate efficiently.

Palantir Foundry centers on user accessibility, data governance, and real-time capabilities, streamlining processes with low-code/no-code development. It supports comprehensive data analysis and integration, enhanced by digital twin features that align virtual and physical interactions. Despite high costs and performance challenges with large datasets, it remains a prime choice for sectors needing structured and unstructured data integration. Key areas include robust data security, lineage tracking, and predictive analytics, promoted through a unified management platform adaptable to diverse needs.

What are the key features of Palantir Foundry?

User-friendly interface enabling easy data governance and automation.
Real-time integration with strong data analysis and collaboration tools.
Low-code/no-code development to widen accessibility.
Digital twin capabilities for bi-directional process integration.
Strong data lineage, predictive analytics, and visualization tools.
Flexibility and customization options.

What benefits and ROI could reviews highlight?

Improved decision-making through enhanced data visibility.
Increased efficiency with automated data processes.
Broader accessibility to data insights via low-code options.
Enhanced collaboration and integration between departments.
Potential cost savings through streamlined operations.

In manufacturing, Palantir Foundry aids in engineering pipeline models and semantic frameworks, while utilities utilize its analytics to enhance service delivery. Insurance firms leverage its capability to assess and predict customer behavior. Throughout these industries, Foundry integrates across cloud environments, bridging structured and unstructured data from various sources.

Palantir

Sample Customers

Qatar Development Bank, GuideWell, Skanderborg Music Festival

Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense

Buyer's Guide

IBM Cloud Pak for Data vs. Palantir Foundry

April 2026

Free Report: IBM Cloud Pak for Data vs. Palantir Foundry

Find out what your peers are saying about IBM Cloud Pak for Data vs. Palantir Foundry and other solutions. Updated: April 2026.

DOWNLOAD NOW

895,272 professionals have used our research since 2012.

See our IBM Cloud Pak for Data vs. Palantir Foundry report.

See our list of best Data Integration vendors.

We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.