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Azure Data Factory 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

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
90
Ranking in other categories
Cloud Data Warehouse (3rd)
Palantir Foundry
Ranking in Data Integration
19th
Average Rating
7.6
Reviews Sentiment
7.1
Number of Reviews
15
Ranking in other categories
IT Operations Analytics (9th), Supply Chain Analytics (1st), Cloud Data Integration (14th), Data Migration Appliances (4th), Data Management Platforms (DMP) (2nd), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of March 2025, in the Data Integration category, the mindshare of Azure Data Factory is 10.0%, down from 12.9% compared to the previous year. The mindshare of Palantir Foundry is 2.7%, up from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.
Rama Subba Reddy Thavva - PeerSpot reviewer
A low-code/no-code platform with a user-friendly UI
We couldn't implement or use some of the latest functionalities, like Spark. Palantir Foundry is scalable, but it is costly compared to other cloud providers. The solution is more suitable for small and medium businesses. It might be difficult for large enterprises. I rate the solution’s scalability 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

"It is a complete ETL Solution."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."
"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"The data lineage is great."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"The virtualization tool is useful."
"Great features available in one tool."
"The solution offers very good end-to-end capabilities."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"The AI engine that comes with Palantir Foundry is quite interesting."
 

Cons

"We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"When working with AWS, we have noticed that the difference between ADF and AWS is that AWS is more customer-focused. They're more responsive compared to any other company. ADF is not as good as AWS, but it should be. If AWS is ten out of ten, ADF is around eight out of ten. I think AWS is easier to understand from the GUI perspective compared to ADF."
"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."
"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."
"The solution could use more online documentation for new users."
"The frontend capabilities of Palantir Foundry could be improved."
"Cost of this solution is quite high."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"The workflow could be improved."
"The solution’s data security could be improved."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
 

Pricing and Cost Advice

"ADF is cheaper compared to AWS."
"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
"I don't see a cost; it appears to be included in general support."
"The solution is cheap."
"The solution's pricing is competitive."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"Understanding the pricing model for Data Factory is quite complex."
"Product is priced at the market standard."
"It's expensive."
"The solution’s pricing is high."
"Palantir Foundry is an expensive solution."
"Palantir Foundry has different pricing models that can be negotiated."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Computer Software Company
12%
Manufacturing Company
9%
Healthcare Company
7%
Manufacturing Company
14%
Financial Services Firm
10%
Computer Software Company
10%
Government
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

How do you select the right cloud ETL tool?
AWS Glue and Azure Data factory for ELT best performance cloud services.
How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
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. ...
 

Overview

 

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa
Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Find out what your peers are saying about Azure Data Factory vs. Palantir Foundry and other solutions. Updated: March 2025.
842,296 professionals have used our research since 2012.