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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
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
93
Ranking in other categories
Cloud Data Warehouse (2nd)
Palantir Foundry
Ranking in Data Integration
12th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
17
Ranking in other categories
IT Operations Analytics (10th), Supply Chain Analytics (1st), Cloud Data Integration (11th), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of February 2026, in the Data Integration category, the mindshare of Azure Data Factory is 3.0%, down from 9.8% compared to the previous year. The mindshare of Palantir Foundry is 2.1%, down from 2.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Market Share Distribution
ProductMarket Share (%)
Azure Data Factory3.0%
Palantir Foundry2.1%
Other94.9%
Data Integration
 

Featured Reviews

KandaswamyMuthukrishnan - PeerSpot reviewer
Director at a computer software company with 1,001-5,000 employees
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.
SR
Architect at L&T Technology Services
Finds security and customization features impressive, although cost concerns persist
My experience with Palantir Foundry and Azure has been good. Palantir Foundry is costly, but Azure is open, which allows for easier experimentation. Being a closed product, Palantir Foundry is difficult to practice offline unless we have an enterprise edition. However, it is very secure compared to other platforms. Palantir Foundry's best features include security, built-in features, low-code, no-code platform, and ease of use. The collaborative workspaces within Palantir Foundry contribute to team efficiency and project outcomes through seamless operation. The ease of customization is particularly notable. I have worked with the data lineage feature in Palantir Foundry, which comes by default. We simply need to tick the checkbox and make necessary configuration changes within the system itself. We do not need to procure another lineage platform as Palantir Foundry has its own built-in features for data lineage, data governance, and data security. The lineage feature helps enhance our data management practices by allowing us to understand the origin of data, track all activities happening on the data, identify users and consumers, and monitor how it flows across the system. This makes it easier to generate reports based on the lineage database. 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. Using the AIP library within Palantir Foundry helps us develop quick resolutions for predictive models and analytics.

Quotes from Members

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

Pros

"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"The data copy template is a valuable feature."
"I can do everything I want with SSIS and Azure Data Factory."
"In terms of my personal experience, it works fine."
"Azure Data Factory became more user-friendly when data-flows were introduced."
"The data flows were beneficial, allowing us to perform multiple transformations."
"We haven't had any issues connecting it to other products."
"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."
"The virtualization tool is useful."
"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."
"The solution offers very good end-to-end capabilities."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"The interface is really user-friendly."
"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."
"I rate Palantir Foundry a ten out of ten."
"The security is also excellent. It's highly granular, so the admins have a high degree of control, and there are many levels of security. That worked well. You won't have an EDC unless you put everything onto the platform because it is its own isolated thing."
 

Cons

"Azure Data Factory's pricing in terms of utilization could be improved."
"Some of the optimization techniques are not scalable."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"There is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration."
"There are limitations when processing more than one GD file."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"I have not found any real shortcomings within the product."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"If you want to create new models on specific data sets, computing that is quite costly."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"The solution's visualization and analysis could be improved."
"Some error messages can be very cryptic."
"The startup pricing is high, causing concern despite being cost-effective in terms of total cost of ownership."
"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."
"The solution could use more online documentation for new users."
 

Pricing and Cost Advice

"The pricing is a bit on the higher end."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"The price you pay is determined by how much you use it."
"Understanding the pricing model for Data Factory is quite complex."
"The solution's pricing is competitive."
"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
11%
Manufacturing Company
9%
Government
6%
Manufacturing Company
14%
Financial Services Firm
10%
Government
8%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise19
Large Enterprise57
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 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...
What advice do you have for others considering Palantir Foundry?
Palantir Foundry is an excellent product for data engineering. On a scale of one to 10, I would rate Palantir Foundry a 9.
 

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: February 2026.
881,565 professionals have used our research since 2012.