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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
92
Ranking in other categories
Cloud Data Warehouse (2nd)
Palantir Foundry
Ranking in Data Integration
14th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
17
Ranking in other categories
IT Operations Analytics (9th), Supply Chain Analytics (1st), Cloud Data Integration (12th), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of October 2025, in the Data Integration category, the mindshare of Azure Data Factory is 5.2%, down from 11.0% compared to the previous year. The mindshare of Palantir Foundry is 3.1%, up from 2.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory5.2%
Palantir Foundry3.1%
Other91.7%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.
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

"Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."
"I am one hundred percent happy with the stability."
"We have found the bulk load feature very valuable."
"The valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."
"The most valuable feature of this solution would be ease of use."
"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."
"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."
"The interface is really user-friendly."
"It's scalable."
"The virtualization tool is useful."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"Great features available in one tool."
"The solution offers very good end-to-end capabilities."
"Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration."
"I like the data onboarding to Palantir Foundry and ETL creation."
 

Cons

"Data Factory's performance during heavy data processing isn't great."
"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."
"The pricing scheme is very complex and difficult to understand."
"Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"The product's technical support has certain shortcomings, making it an area where improvements are required."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"The solution's visualization and analysis could be improved."
"If you want to create new models on specific data sets, computing that is quite costly."
"The workflow could be improved."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"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."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"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."
"The startup pricing is high, causing concern despite being cost-effective in terms of total cost of ownership."
 

Pricing and Cost Advice

"The pricing is a bit on the higher end."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"ADF is cheaper compared to AWS."
"I would not say that this product is overly expensive."
"Pricing is comparable, it's somewhere in the middle."
"The price you pay is determined by how much you use it."
"I would rate Data Factory's pricing nine out of ten."
"The licensing is a pay-as-you-go model, where you pay for what you consume."
"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%
Government
7%
Manufacturing Company
13%
Financial Services Firm
10%
Government
7%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise55
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise5
Large Enterprise8
 

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?
Apart from the pricing and offline availability issues, improvements are needed in Palantir Foundry's costing factor. Cost-wise, it is not open for everybody, and they are not exposing anything out...
What is your primary use case for Palantir Foundry?
One of the leading European manufacturing plants uses Palantir Foundry for manufacturing interior parts of various car brands such as Honda, Hyundai, Ford, Mercedes-Benz, and BMW. This involves hig...
 

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: September 2025.
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