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Azure Data Factory vs Palantir Gotham comparison

 

Comparison Buyer's Guide

Executive Summary

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
5th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
96
Ranking in other categories
Cloud Data Warehouse (7th)
Palantir Gotham
Ranking in Data Integration
55th
Average Rating
8.0
Reviews Sentiment
7.3
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 7.2% compared to the previous year. The mindshare of Palantir Gotham is 0.8%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.3%
Palantir Gotham0.8%
Other96.9%
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.
WH
Manager at a tech services company with 201-500 employees
A seamless all-in-one solution
This solution is seamless. From one platform, we can do just about anything. With other solutions, you'll need a separate platform for data ingestion, manipulation, etc. Then you'll need another tool for reporting. Palantir Gotham literally does it all. It generates a report regardless of the format. It can seamlessly generate it after the data has been collected.

Quotes from Members

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

Pros

"Azure Data Factory is a very easy to use ETL tool for loading and transforming data from one location to another."
"It's a good tool, a good product that does what it's supposed to do well, which is ingesting data from a source to your target, to another cloud, to another source."
"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"The data copy template is a valuable feature, and with the pipeline template, it takes only a few clicks for the on-premises data to come in."
"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS."
"We use the solution to move data from on-premises to the cloud."
"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."
"The solution is okay."
"This solution is seamless. From one platform, we can do just about anything."
 

Cons

"Some prebuilt data source or data connection aspects are generic."
"I would like to be informed about the changes ahead of time, so we are aware of what's coming."
"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"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."
"I do not have any notes for improvement."
"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."
"Data Factory's performance during heavy data processing isn't great."
"I think there should be less coding involved. Currently, using it involves a tremendous amount of coding."
 

Pricing and Cost Advice

"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."
"Azure Data Factory gives better value for the price than other solutions such as Informatica."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"The cost is based on the amount of data sets that we are ingesting."
"Product is priced at the market standard."
"Pricing appears to be reasonable in my opinion."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"Understanding the pricing model for Data Factory is quite complex."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
11%
Manufacturing Company
9%
Computer Software Company
9%
Construction Company
7%
Government
13%
Outsourcing Company
11%
Computer Software Company
8%
Retailer
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise21
Large Enterprise63
No data available
 

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...
Ask a question
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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
Team Rubicon, CGI
Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration. Updated: July 2026.
909,563 professionals have used our research since 2012.