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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

"The most valuable feature is the ease in which you can create an ETL pipeline."
"It's extremely consistent."
"Data Factory allows you to pull data from multiple systems, transform it according to your business needs, and load it into a data warehouse or data lake."
"Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness."
"It is very modular; it works well, is very flexible, and you can easily bring in outside capabilities and build any features you want."
"The trigger scheduling options are decently robust."
"Synapse was the better choice for us to implement, as it has a lot of out-of-the-box connectors that we can utilize for data transformation and organization."
"This is an excellent tool for pipeline orchestration; connecting the different components and activities as well as gathering data."
"This solution is seamless. From one platform, we can do just about anything."
 

Cons

"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."
"Lacks in-built streaming data processing."
"The one element of the solution that we have used and could be improved is the user interface."
"There is one particular problem with Azure Data Factory. When you have a parent-to-child relationship and the child has one more relationship, creating a hierarchy situation, there are issues."
"There are performance issues, particularly with the underlying compute, which should be configurable."
"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."
"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."
"I think there should be less coding involved. Currently, using it involves a tremendous amount of coding."
 

Pricing and Cost Advice

"The solution is cheap."
"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 rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"I would not say that this product is overly expensive."
"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."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"ADF is cheaper compared to AWS."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
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...
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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.
908,834 professionals have used our research since 2012.