Azure Data Factory vs Palantir Foundry comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Azure Data Factory
Ranking in Data Integration
1st
Average Rating
8.0
Number of Reviews
81
Ranking in other categories
Cloud Data Warehouse (3rd)
Palantir Foundry
Ranking in Data Integration
11th
Average Rating
7.6
Number of Reviews
14
Ranking in other categories
IT Operations Analytics (5th), 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 June 2024, in the Data Integration category, the mindshare of Azure Data Factory is 9.6%, down from 13.6% compared to the previous year. The mindshare of Palantir Foundry is 1.6%, down from 3.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
Unique Categories:
Cloud Data Warehouse
13.6%
IT Operations Analytics
2.7%
Supply Chain Analytics
50.0%
 

Featured Reviews

Zubair_Ahmed - PeerSpot reviewer
Nov 30, 2023
Seamless cloud-based data integration providing a versatile platform with scalable data processing, diverse data connectors, and comprehensive monitoring and management capabilities
My task involves extracting data from a source, performing necessary transformations, and subsequently loading the data into a target destination, which happens to be Azure SQL Database The company is experiencing significant benefits as one of our customers is successfully implementing the…
RD
Nov 22, 2022
Effectively processes data within a single management platform
Our company uses the solution to elaborate off PySpark. We run PySpark scripts for our products but use the solution to leverage the workflows that automatically run time bound and trigger bound. When a data trigger is there, the solution executes and the script starts running.  Our scripts were…

Quotes from Members

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

Pros

"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."
"We have been using drivers to connect to various data sets and consume data."
"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."
"The function of the solution is great."
"The initial setup is very quick and easy."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."
"Its integrability with the rest of the activities on Azure is most valuable."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"The virtualization tool is useful."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"The AI engine that comes with Palantir Foundry is quite interesting."
"The interface is really user-friendly."
"The solution offers very good end-to-end capabilities."
"The data lineage is great."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
 

Cons

"The Microsoft documentation is too complicated."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"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's cost is too high."
"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."
"The product's technical support has certain shortcomings, making it an area where improvements are required."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"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 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 frontend capabilities of Palantir Foundry could be improved."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"Some error messages can be very cryptic."
"Difficult to receive data from external sources."
"If you want to create new models on specific data sets, computing that is quite costly."
"The solution's visualization and analysis could be improved."
 

Pricing and Cost Advice

"The solution's pricing is competitive."
"It's not particularly expensive."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"The price is fair."
"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."
"Understanding the pricing model for Data Factory is quite complex."
"I would rate Data Factory's pricing nine out of ten."
"I don't see a cost; it appears to be included in general support."
"Palantir Foundry has different pricing models that can be negotiated."
"It's expensive."
"The solution’s pricing is high."
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Top Industries

By visitors reading reviews
Computer Software Company
13%
Financial Services Firm
13%
Manufacturing Company
8%
Healthcare Company
7%
Manufacturing Company
12%
Financial Services Firm
11%
Computer Software Company
11%
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?
Palantir Foundry is very good for someone technical. The tool still needs to work on the non-technical part, where people can use its flexibility. The business user should not end up writing huge q...
What is your primary use case for Palantir Foundry?
The AI engine that comes with Palantir Foundry is quite interesting. We have a lot of data from various trials and analyses. We need a machine learning and analytical feature that can push huge amo...
 

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: May 2024.
787,817 professionals have used our research since 2012.