Palantir Foundry vs SAP Data Hub [EOL] comparison

Why PeerSpot?

The compared Palantir and SAP solutions aren't in the same category. Palantir is ranked #3 in DI , with an average rating of 8.2, and holds a 2.2% mindshare in the category. Additionally, 93% of Palantir users are willing to recommend the solution, compared to 66% of SAP users who would recommend it.

Palantir Foundry

Read 62 Palantir Foundry reviews

20,123 Views
8,250 Comparison Views

93% willing to recommend

SAP Data Hub [EOL]

Read 3 SAP Data Hub [EOL] reviews

66% willing to recommend

Palantir Foundry

SAP Data Hub [EOL]

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Palantir Foundry and SAP Data Hub [EOL] based on real PeerSpot user reviews.

Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: October 2026).

Buyer's Guide

Data Integration

October 2026

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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

Palantir Foundry

Average Rating

8.0

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Integration (3rd), IT Operations Analytics (4th), Supply Chain Analytics (1st), Cloud Data Integration (5th), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)

SAP Data Hub [EOL]

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Featured Reviews

reviewer2846265

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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Vijaya Macherla

GTM Lead at Capgemini

The solution is seamless, but the database sometimes leads to confusion

We used to have multiple different kinds of databases, which internally, had different compliance levels. Retention management is very different now. If the policy is live and the claim has been completed, I couldn't archive the claim. I needed to keep a reference integrity of that claim and understand which policy paid out the claim. With this solution, the policy came in six months ago and qualified for archiving. The claim had been paid and in every environment, the claim had been closed, including the reporting system, the claims system, etc. With the payment set gateway, I can just go and archive. But, we had a hard time during this process. I rate the overall solution a seven out of ten.

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Quotes from Members

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

Pros

"Palantir Foundry has positively impacted our organization by making our processes straightforward and fast-moving, especially with features like AIP, an AI-powered assistance, and the low-code ability to create transformations quickly, which has benefited me significantly."

"This product has all the various components for getting data, transforming it and visually creating the dashboards without the need to integrate things and no need to check the compatibility."

"From my experience with Palantir Foundry, the most useful feature is its no-code, low-code environment, allowing me to develop applications without extensive coding, unlike my past as an Oracle developer where I had to write code for various functions."

"Palantir Foundry has dramatically helped us in terms of project costing because earlier we had our own React developers team from offshore, and now with the AIP capabilities launched on the platform, we have completely avoided the need for a dedicated team, which has been very helpful in terms of cost management and reducing team size."

"Encapsulates all the components without the requirement to integrate or check compatibility."

"I appreciate multiple aspects of Palantir Foundry, starting with the clean architecture and clean UI, and I really value how easily I can create and test Python and PySpark scripts, trace data lineage to debug issues, monitor daily pipelines and health checks, and quickly build very interactive Workshop applications, all supported by a clean and informative Resource Management UI that helps track costs and data usage."

"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."

"Previously, the team used to take more than a week to gather data for a particular entity and make it ready for downstream use cases, and that was reduced from seven days to close to 30 to 45 minutes because everything was automated using pipelines and schedules."

More Palantir Foundry pros

"Having this solution enables us to approach our clients to upgrade their databases, and we upgrade them according to their business requirements."

"The most valuable feature is the S/4HANA 1909 On-Premise"

"Its connection to on-premise products is the most valuable. We mostly use the on-premise connection, which is seamless. This is what we prefer in this solution over other solutions. We are using it the most for the orchestration where the data is coming from different categories. Its other features are very much similar to what they are giving us in open source. Their push-down approach is the most advantageous, where they push most of the processing on to the same data source. This means that they have a serverless kind of thing, and they don't process the data inside a product such as Data Hub. They process the data from where the data is coming out. If it is coming from HANA, to capture the data or process it for analytics, orchestration, or management, they go to the HANA database and give it out. They don't process it on Data Hub. This push-down approach increases the processing speed a little bit because the data is processed where it is sitting. That's the best part and an advantage. I have used another product where they used to capture the data first and then they used to process it and give it. In Data Hub, it is in reverse. They process it first and give it, and then they put their own manipulations. They lead in terms of business functions. No other solution has business functions already implemented to perform business analysis. They have a lot of prebuilt business functions for machine learning and orchestration, which we can use directly to get an analysis out from the existing data. Most of the data is sitting as enterprise data there. That's a major advantage that they have."

"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."

"They lead in terms of business functions, and no other solution has business functions already implemented to perform business analysis, with a lot of prebuilt business functions for machine learning and orchestration that we can use directly to get an analysis out from the existing enterprise data."

Cons

"I believe that the AI or agent needs improvement because sometimes we face difficulties when looking for solutions, and when we ask the agent, AIP, it does not understand our queries and occasionally provides wrong solutions."

"However, I observe a potential drawback concerning market trends; as software becomes more accessible with individuals developing applications independently, there is a risk posed to Palantir Foundry, which combines multiple core functionalities."

"With Palantir Foundry, it is a part of the user tools that they provide. Their AI Assist that they use is something I have found that sometimes I get better results for when I do need help and aid."

"The workflow could be improved. Although it works rather seamlessly, the workflow is too complicated sometimes."

"I want to pass the certification of Palantir Foundry because it is not easy to find the information regarding this certification, making it not accessible for many people, which I think is not good."

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

"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."

"When we were using ETL with Palantir Foundry, we found we had less freedom compared to Cloudera, where we had more liberty in using various configuration parameters of Spark, allowing us to tune our jobs accordingly."

More Palantir Foundry cons

"In 2018, connecting it to outside sources, such as IoT products or IoT-enabled big data Hadoop, was a little complex. It was not smooth at the beginning. It was unstable. It took a lot of time for the initial data load. Sometimes, the connection broke, and we had to restart the process, which was a major issue, but they might have improved it now. It is very smooth with SAP HANA on-premise system, SAP Cloud Platform, and SAP Analytics Cloud. It could be because these are their own products, and they know how to integrate them. With Hadoop, they might have used open-source technologies, and that's why it was breaking at that time. They are providing less embedded integration because they want us to use their other products. For example, they don't want to go and remove SAP Analytics Cloud and put everything in Data Hub. They want us to use SAP Analytics Cloud somewhere else and not inside the Data Hub. On the integration part, it lacks real-time analytics, and it is slow. They should embed the SAP Analytics Cloud inside Data Hub or support some kind of analysis. They do provide some analysis, but it is not extensive. They are moreover open source. So, we need a lot of developers or data scientists to go in and implement Python algorithms. It would be better if they can provide their own existing algorithms and give some connections and drop-down menus to go and just configure those. It will make things really quick by increasing the embedded integrations. It will also improve the process efficiency and processing power. Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this. In terms of technology and performance, it is a little slow as compared to Microsoft and other data orchestration products. I haven't used other products, but I have read about those products, their settings, and the milliseconds that they do. In Azure Purview, they say that they can copy, manage, or transform the data within milliseconds. They say that they can transform 100 gigabytes of data within three to five seconds, which is something SAP cannot do. It generally takes a lot of time to process that much amount of data. However, I have never tested out Azure."

"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."

"Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this."

"The company has everything offshore."

Pricing and Cost Advice

"Palantir Foundry is an expensive solution."

"It's expensive."

"Palantir Foundry has different pricing models that can be negotiated."

"The solution’s pricing is high."

"The Cloud is very expensive, but SAP HANA previous service is okay."

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Top Industries

By visitors reading reviews

Manufacturing Company

14%

Financial Services Firm

10%

Comms Service Provider

Outsourcing Company

15%

Manufacturing Company

13%

Financial Services Firm

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	7
Large Enterprise	51

No data available

Questions from the Community

What needs improvement with Palantir Foundry?

The Workshop application could be improved because it is not very customizable, but it is still very strong. We also have the React OSK apps, but it does not allow the inbuilt applications such as ...

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What is your primary use case for Palantir Foundry?

My main use case for Palantir Foundry is to solve business problems, such as in healthcare. I also worked on a project for a law firm where thousands of PDFs were coming in, and we needed to check ...

See all answers

What advice do you have for others considering Palantir Foundry?

I believe they should get started by completing all the free certificates, then they could apply to the paid certificates to get a master of Palantir Foundry, solve some real use cases, do examples...

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Product Reports

Buyer's Guide

Palantir Foundry

October 2026

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Buyer's Guide

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Overview

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

The SAP® Data Hub solution enables sophisticated data operations management. It gives you the capability and flexibility to connect enterprise data and Big Data and gain a deep understanding of data and information processes across sources and systems throughout the distributed landscape. The unified solution provides visibility and control into data opportunities, integrating cloud and on-premise information and driving data agility and business value. Distributed processing power enables greater speed and efficiency.

SAP

Sample Customers

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

Kaeser Kompressoren, HARTMANN

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