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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:
 

ROI

Sentiment score
5.1
Users see improved efficiency and ROI with IBM Cloud Pak for Data, streamlining management and boosting compliance and satisfaction.
Sentiment score
5.1
Users report time and cost savings with Palantir Foundry, but quantifying ROI and financial specifics remains challenging.
We have been able to drive responsible, transparent, and explainable AI workflow to operationalize AI and mitigate risk and regulatory compliance easily.
Senior Data Analyst at Wipro Limited
It is easy to collect, organize, and analyze data no matter where it is, hence being able to make data-driven decisions.
Engineer at Turner Construction
With traditional development requiring many specialized roles, Palantir Foundry allows us to operate efficiently with fewer personnel.
Data Engineering Specialist at LTM
We saved approximately 20 to 35 percent in man-hours needed and the timing improved our project timelines by approximately 50 to 55 percent.
Consultant at a tech vendor with 1,001-5,000 employees
One clear example was the pipeline optimization I mentioned, where we reduced execution time by thirty to forty percent.
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
 

Customer Service

Sentiment score
7.1
IBM Cloud Pak for Data's support is responsive, rated highly, and cost-effective, but lacks local language options and has occasional delays.
Sentiment score
6.2
Palantir Foundry's customer service is competent and proactive, though experiences vary based on contract and user needs.
I rate the technical support from IBM a nine out of ten because the support has been very top-notch, unparalleled, and also very professional.
Manager at teshama
Cloud Pak is a complicated system, and it's often difficult to find the right resource in IBM to help with specific issues.
Data asset management engineer at a tech services company with 1-10 employees
The customer support for IBM Cloud Pak for Data is great and responsive.
Engineer at Turner Construction
They are knowledgeable, and their boot camps demonstrate solutions in just three days, which typically takes months or years.
Enterprise Architect at a mining and metals company with 10,001+ employees
When I seek help regarding code in Slate, it can take considerable time for the team to find the right answer or documentation, especially since the responses depend on the level of support provided, and specific queries regarding coding usually require reaching out to more experienced developers.
Data Analyst at BP Exploration Caspian Sea Ltd
The support staff are extremely knowledgeable and good at what they are doing.
Operations And Integration Chief at a aerospace/defense firm with 10,001+ employees
 

Scalability Issues

Sentiment score
6.6
IBM Cloud Pak for Data is scalable, efficiently managing growth and large data, with high resource use noted.
Sentiment score
6.1
Palantir Foundry is praised for scalability, flexibility, and adaptability across business sizes, despite cloud cost concerns.
I have not noticed any downtime or lagging, especially when dealing with large data, so it is relatively very scalable.
Senior Data Analyst at Wipro Limited
IBM Cloud Pak for Data's scalability is very good; it can be used by any size of organization.
Engineer at Turner Construction
For scalability, I rate it a nine out of ten because it is a very scalable solution that has been able to handle my organization's growth efficiently.
Manager at teshama
We work with large volumes of healthcare data, and it has been able to handle all the large-scale ingestion, transformation, and distributed processing workflows effectively.
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
For scalability, I would rate it ten out of ten because you have a lot of flexibility.
Associate Vice President at a insurance company with 10,001+ employees
Regarding scalability, if you have billions and trillions of records, Palantir Foundry accommodates ETL pipelines with a dedicated compute profile.
Data Engineering Specialist at LTM
 

Stability Issues

Sentiment score
7.8
IBM Cloud Pak for Data is stable with positive performance and integration, though scalability improvements are desired by some users.
Sentiment score
7.7
Palantir Foundry is stable and reliable, with minor issues quickly resolved, though some suggest marketing may overstate capabilities.
The overall performance of IBM Cloud Pak for Data, particularly with IBM DataStage for ETL processes, is very good.
Sales Director at Jordan Business Systems
Live data streaming is very hard and it keeps breaking, so it is not very stable and depends a lot on the satellite network.
Product Manager
I get more technical support from Palantir.
Data Development Manager at a healthcare company with 5,001-10,000 employees
Palantir Foundry has been a stable and reliable enterprise platform.
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
 

Room For Improvement

IBM Cloud Pak for Data needs better integration, enhanced performance, simplified setup, cost management, and improved analytics for broader adoption.
Palantir Foundry needs enhanced training, cost-efficiency, ease of use, integration, automation, and AI for improved user experience.
Setting up the hybrid and multi-cloud environments is a long job and it takes time.
Senior Data Analyst at Wipro Limited
IBM Cloud Pak for Data can be improved because processing speeds are sometimes slow.
Engineer at Turner Construction
To improve IBM Cloud Pak for Data, I suggest more out-of-the-box integration.
Senior Project Manager at EY
The platform is extremely capable, but improvements around usability, debugging experience, DevOps flexibility, and ecosystem openness would make it even more effective for enterprise engineering teams.
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
I want to build conversational BI or conversational agents quickly that can connect to MCPs, and other MCPs that I can communicate with in Palantir Foundry, which are areas to advance forward.
Principal Architect at HCLTech
An improvement would be that in case of any changes done by the Palantir team, those changes need to be tested thoroughly so there are no downstream impacts, ensuring that the business is not affected by any modifications in the system.
Engineer, Data Engineering at GlobalFoundries
 

Setup Cost

IBM Cloud Pak for Data is costly, suitable for large enterprises, with pricing based on usage and deployment.
Palantir Foundry's high cost is justified for enterprises by reduced development needs and centralized capabilities despite complex licensing.
The setup cost is very expensive.
Data asset management engineer at a tech services company with 1-10 employees
Regarding my experience with pricing, setup cost, and licensing, for a small organization, the price might be relatively high, but for huge enterprises such as ours, the price is relatively affordable.
Senior Data Analyst at Wipro Limited
The list price is high, but the flexibility in pricing is adequate.
Solution Manager at Intalion
Its high initial pricing can be intimidating, but it becomes cost-effective as it reduces the need for a development team.
Enterprise Architect at a mining and metals company with 10,001+ employees
In terms of getting a contractor to work on that, I would probably say it is more expensive because there are fewer people with that skillset compared to, say, Databricks or Azure.
Data Development Manager at a healthcare company with 5,001-10,000 employees
We can consult it in the right way regarding Palantir Foundry use, as it is still a gray area right now concerning costing.
Principal Architect at HCLTech
 

Valuable Features

IBM Cloud Pak for Data enhances productivity with AI tools, data governance, and seamless integration across hybrid and multi-cloud environments.
Palantir Foundry enhances data-driven decisions with strong AI, user-friendly tools, robust security, and seamless integration for all users.
From there, I can work my way into a more granular level, applying all of that information on top of my actual data to understand what my data looks like, where it came from, and where it went wrong, managing it throughout the cycle.
Data asset management engineer at a tech services company with 1-10 employees
The benefits of choosing IBM Cognos, in addition to saving on cost, include having institutional knowledge about maintaining this infrastructure and enough people who have developed on Cognos in the past, which creates comfort in its use.
EDW Manager at a university with 1,001-5,000 employees
We have been able to save approximately 80 percent of our time. We are not doing data analysis manually, so this relieves our data department of dealing with data.
Senior Data Analyst at Wipro Limited
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.
Architect at L&T Technology Services
The main advantage is you can decentralize the analytics, and you will have everything in one place, so that you do not need to rely on multiple departments working on different tools.
Associate Vice President at a insurance company with 10,001+ employees
The low-code solutions made our lives easier because not everybody is too technical to get started and the barrier to entry is very low.
Consultant at a tech vendor with 1,001-5,000 employees
 

Categories and Ranking

IBM Cloud Pak for Data
Ranking in Data Integration
18th
Average Rating
8.2
Reviews Sentiment
6.1
Number of Reviews
21
Ranking in other categories
Data Virtualization (3rd)
Palantir Foundry
Ranking in Data Integration
3rd
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
62
Ranking in other categories
IT Operations Analytics (4th), Supply Chain Analytics (1st), Cloud Data Integration (4th), Data Migration Appliances (2nd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of July 2026, in the Data Integration category, the mindshare of IBM Cloud Pak for Data is 1.1%, down from 1.9% compared to the previous year. The mindshare of Palantir Foundry is 2.1%, down from 3.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Palantir Foundry2.1%
IBM Cloud Pak for Data1.1%
Other96.8%
Data Integration
 

Featured Reviews

ArchanaSingh - PeerSpot reviewer
Senior Data Analyst at Wipro Limited
Collaborative data platform has transformed analytics and now drives faster decisions
The best features IBM Cloud Pak for Data offers include robust data visualization, centralized data analytics, data reliability, and compatibility with hybrid and multi-cloud environments. The compatibility with hybrid and multi-cloud environments has helped our organization as data visualization is very simple. Migrations, reading, analysis, and data management from other sources are performed without problems of requirements. We have a team of experts in IBM Cloud Pak for Data to maintain security and correct data management easily. I find this cloud excellent for visualizing and managing data across networks and also fulfilling fastest data storage, making it less complex and completely improving productivity in my organization. Everything is managed in multiple environments without any problem. IBM Cloud Pak for Data has positively impacted my organization, and I have noticed some improvement since we started using this tool. Configuration with hybrid and multi-cloud environments has been very seamless and easy. It is a robust platform capable of working with multiple data sources where we gain insights to make data-driven decisions easily. It automates data analysis for quick and better performance. We have seen improvements in analysis and data correction from multiple sources. Our productivity in the company is growing, thanks to the data analysis team. We have also seen a robust hybrid and multi-cloud access system working seamlessly. I can share specific outcomes that show how productivity has grown and how performance has improved since the data is automated, and the analysis is done much faster, saving us a lot of time. We have been able to save approximately 80 percent of our time. We are not doing data analysis manually, so this relieves our data department of dealing with data. We have been relieved of a lot of duties, and now we are able to focus on other strategic tasks. Our productivity has greatly increased since we are able to make concrete and data-driven decisions easily.
reviewer2846265 - PeerSpot reviewer
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
Unified healthcare pipelines have improved data trust and accelerated operational decisions
One challenge regarding how Palantir Foundry can be improved is the learning curve. Foundry has a very broad ecosystem with Ontology, Pipeline Builder, Code Repositories, and AI integrations. For new engineers or business users onboarding, it can take time, especially if they are coming from more traditional data platforms. Better documentation, simplified onboarding paths, and more beginner-friendly examples would help accelerate adoption. Another area is debugging complexity. While lineage and monitoring are strong features, troubleshooting deeply interconnected pipelines can still become difficult in a large enterprise environment. Sometimes error logs and pipeline failure messages could be more descriptive or developer-friendly, especially for distributed PySpark jobs. Another pain point is customization limitations in certain UI-driven components. While low-code tools are great for rapid development, highly customized workflows sometimes still require engineering workarounds or deeper technical implementation. The platform is extremely capable, but improvements around usability, debugging experience, DevOps flexibility, and ecosystem openness would make it even more effective for enterprise engineering teams.
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Manufacturing Company
10%
Computer Software Company
6%
University
5%
Manufacturing Company
14%
Financial Services Firm
10%
Government
7%
University
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business10
Large Enterprise20
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise7
Large Enterprise50
 

Questions from the Community

What is your experience regarding pricing and costs for IBM Cloud Pak for Data?
My experience with pricing, setup cost, and licensing is that the cost of the product can be a bit higher, especially for a company working on a tight budget.
What needs improvement with IBM Cloud Pak for Data?
One of the improvements I think should be made to IBM Cloud Pak for Data is that the cost of the product is a bit higher. Besides cost, I think something that is needed for improvement is that more...
What is your primary use case for IBM Cloud Pak for Data?
My main use case for IBM Cloud Pak for Data is that it is fully scalable and a scalable platform for data. I use it to provide data solutions for my customers. I also use it to provide various indu...
What needs improvement with Palantir Foundry?
I think the things that I do not like about Palantir Foundry is not a Palantir issue so much as it is from my company side and what they have commissioned for and have not commissioned for. With Pa...
What is your primary use case for Palantir Foundry?
I use Palantir Foundry to ingest data and create visualizations for decisions.
 

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: June 2026.
905,601 professionals have used our research since 2012.