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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
4th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
94
Ranking in other categories
Cloud Data Warehouse (5th)
Palantir Gotham
Ranking in Data Integration
52nd
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 May 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.4%, down from 8.6% compared to the previous year. The mindshare of Palantir Gotham is 0.8%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Azure Data Factory2.4%
Palantir Gotham0.8%
Other96.8%
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

"I like that it's a monolithic data platform. This is why we propose these solutions."
"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."
"The initial setup is pretty simple and it can be deployed in a couple of hours."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"The scalability of the product is impressive."
"In terms of my personal experience, it works fine."
"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."
"We use the solution to move data from on-premises to the cloud."
"This solution is seamless; from one platform, we can do just about anything."
"This solution is seamless. From one platform, we can do just about anything."
 

Cons

"The main challenge with implementing Azure Data Factory is that it processes data in batches, not near real-time. To achieve near real-time processing, we need to schedule updates more frequently, which can be an issue. Its interface needs to be lighter."
"The setup and configuration process could be simplified."
"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."
"It would be helpful if they could adjust the data capture feature so that when there are source-side changes ADF could automatically figure it out."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"It can improve from the perspective of active logging."
"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."
"I think there should be less coding involved. Currently, using it involves a tremendous amount of coding."
"I think there should be less coding involved. Currently, using it involves a tremendous amount of coding."
 

Pricing and Cost Advice

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"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."
"The pricing is a bit on the higher end."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"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 solution's pricing is competitive."
"I would rate Data Factory's pricing nine out of ten."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
10%
Manufacturing Company
9%
Government
6%
Government
14%
Computer Software Company
9%
Retailer
9%
Comms Service Provider
7%
 

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, Qlik and others in Data Integration. Updated: May 2026.
894,668 professionals have used our research since 2012.