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Palantir Foundry vs SAP Data Hub comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Palantir Foundry
Average Rating
7.6
Reviews Sentiment
7.2
Number of Reviews
15
Ranking in other categories
Data Integration (12th), IT Operations Analytics (4th), Supply Chain Analytics (1st), Cloud Data Integration (10th), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
SAP Data Hub
Average Rating
7.6
Reviews Sentiment
6.2
Number of Reviews
3
Ranking in other categories
Data Governance (28th), Metadata Management (9th)
 

Mindshare comparison

Palantir Foundry and SAP Data Hub aren’t in the same category and serve different purposes. Palantir Foundry is designed for Data Integration and holds a mindshare of 2.5%, down 3.1% compared to last year.
SAP Data Hub, on the other hand, focuses on Data Governance, holds 1.2% mindshare, down 1.6% since last year.
Data Integration
Data Governance
 

Featured Reviews

Manilal Kasera - PeerSpot reviewer
Transparent with good reliability and good data visibility
The initial setup had a medium level of difficulty. If we go through the documentation, we can learn about what to do. In Palantir, they had a section called Academy, and that Academy was quite useful. If you go through that as a new user, it makes the process easier as you learn what to do. Initially, we didn't have many sources that would help us learn things, so we struggled a bit. In contrast, with Azure and Amazon Cloud, you have many sources from where you would be easily able to learn. You could just Google what you needed with them, as there's so much available documentation online. What was easy was the fact that everything was in one place. With AWS Cloud, there are many applications to support. You can use Glue or Athena, and you have all these other applications. However, with Palantir, everything is easy due to the fact that it is centralized. It's drag and drop and everything is very transparent.
VM
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.

Quotes from Members

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

Pros

"Encapsulates all the components without the requirement to integrate or check compatibility."
"The data lineage is great."
"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."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"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."
"The solution offers very good end-to-end capabilities."
"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."
"The most valuable feature is the S/4HANA 1909 On-Premise"
 

Cons

"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"The frontend capabilities of Palantir Foundry could be improved."
"Some error messages can be very cryptic."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"Difficult to receive data from external sources."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"The solution could use more online documentation for new 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."
"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."
"The company has everything offshore."
 

Pricing and Cost Advice

"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."
"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
11%
Computer Software Company
10%
Government
7%
Computer Software Company
15%
Financial Services Firm
14%
Manufacturing Company
14%
Government
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

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?
The solution’s data security could be improved. We cannot use many Python packages with the solution. We were able to use only a few compatible Python packages.
What is your primary use case for Palantir Foundry?
Our use cases are mostly related to data analytics. We are building some dashboards and ETL pipelines on the Palantir side. Palantir Foundry is a low-code/no-code platform with a user-friendly UI. ...
What do you like most about SAP Data Hub?
SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database.
What needs improvement with SAP Data Hub?
We moved from Oracle. If you're aware of your monitoring system, the RPU market, and the managed system, you should move to HANA, which is an innovative database built by SAP itself. However, this ...
What is your primary use case for SAP Data Hub?
I technically handle the database, like cycle management projects. When transaction data comes in, we see it based on the retention periods. We have to move the data to some secure storage rather t...
 

Learn More

 

Overview

 

Sample Customers

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