Azure Data Factory vs Palantir Gotham comparison

Why PeerSpot?

Microsoft and Palantir are both solutions in the Data Integration category. Microsoft is ranked #6 with an average rating of 8.0, while Palantir is ranked #57. Microsoft holds a 2.2% mindshare in DI, compared to Palantir’s 0.8% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Palantir users who would recommend it.

Azure Data Factory

Read 97 Azure Data Factory reviews

16,078 Views
11,255 Comparison Views

92% willing to recommend

Palantir Gotham

Read 1 Palantir Gotham review

2,781 Views
2,503 Comparison Views

100% willing to recommend

Azure Data Factory

Palantir Gotham

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Azure Data Factory and Palantir Gotham based on real PeerSpot user reviews.

Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: October 2026).

Buyer's Guide

Data Integration

October 2026

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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

6th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (8th)

Palantir Gotham

Ranking in Data Integration

57th

Average Rating

8.0

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.2%, down from 4.4% compared to the previous year. The mindshare of Palantir Gotham is 0.8%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.2%
Palantir Gotham	0.8%
Other	97.0%

Data Integration

Featured Reviews

Kunal Das

Test Engineer at Happiest Minds Technologies

Drag-and-drop pipelines have saved days of work and now automate data movement and backfilling

If the AI features were more improved so that I don't have to provide each and every detail, Azure Data Factory could be improved in a much better way by improving the AI features. For example, if I want to fetch any data from a raw source, I need to provide each and every detail. But if I am just uploading my raw data and if AI will sync with that data, it can analyze that data and give me proper suggestions on how that should be done in a proper way. Automatic suggestions could improve in a much better way. As I have mentioned, the AI features as well as more drag-and-drop activities could be improved. If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity. If I have used one activity, I shouldn't have to remember what activity should I use next. It should give auto-suggestions. That is why I have given a nine out of 10. Currently, I don't know about its governance and security, but in view of its improvement, I think Azure Data Factory should improve in these areas. As I already mentioned, the AI features should be improved. Also, the auto-suggestion features should also improve.

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Wallace Hugh

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.

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Quotes from Members

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

Pros

"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."

"The data flows were beneficial, allowing us to perform multiple transformations."

"Azure Data Factory is easy to use and integrates well, providing good classification to bring data from diverse parts of the data infrastructure, whether from CSV files coming from the Cisco server, MySQL, Excel machines, or local network data from remote files."

"I find that the solution integrates well with cloud technologies, which we are using for different clouds like Snowflake and AWS."

"The support for SAP services and databases, specifically SAP HANA, has been a game-changer for us."

"It works very well with Azure Data Factory to pull the records, parse them quickly and post them in the database and data warehouse."

"This is an excellent tool for pipeline orchestration; connecting the different components and activities as well as gathering data."

"The trigger scheduling options are decently robust."

More Azure Data Factory pros

"This solution is seamless. From one platform, we can do just about anything."

Cons

"Compared to Informatica, it's really crude. I think it's a very crude solution."

"Some known bugs and issues with Azure Data Factory could be rectified."

"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."

"While it has a range of connectors for various systems, such as ERP systems, the support for these connectors can be lacking."

"Data Factory could be improved in terms of data transformations by adding more metadata extractions."

"There is no built-in pipeline exit activity when encountering an error."

"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."

"They should work on optimizing their licensing model and pricing structure."

More Azure Data Factory cons

"I think there should be less coding involved. Currently, using it involves a tremendous amount of coding."

Pricing and Cost Advice

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

"The solution is cheap."

"The cost is based on the amount of data sets that we are ingesting."

"Understanding the pricing model for Data Factory is quite complex."

"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."

More Azure Data Factory pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Manufacturing Company

11%

Financial Services Firm

10%

Outsourcing Company

Computer Software Company

Comms Service Provider

12%

Manufacturing Company

12%

Outsourcing Company

10%

Construction Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	64

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.

See all answers

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...

See all answers

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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Comparisons

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 3% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

SnapLogic vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Palantir Foundry vs Palantir Gotham

Compared 25% of the time

Peregrine vs Palantir Gotham

Compared 7% of the time

SSIS vs Palantir Gotham

Compared 5% of the time

ETL Solutions Transformation Manager vs Palantir Gotham

Compared 5% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Palantir Gotham

Compared 4% of the time

More Palantir Gotham Competitors

Product Reports

Buyer's Guide

Azure Data Factory

November 2026

Download Azure Data Factory product report

Buyer's Guide

Data Integration

October 2026

Download Palantir Gotham product report

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

Microsoft

Palantir Gotham is a data integration and analysis platform designed to enable organizations to manage, interpret, and act on complex data sets. It is widely used for security, intelligence, and operations optimization.

Palantir Gotham offers robust features for integrating disparate data sources, ensuring real-time collaboration and enhancing decision-making processes. It enables users to resolve data silos, derive actionable insights, and streamline workflow with precision and privacy controls. Trusted by government and commercial sectors, it seamlessly delivers on mission-critical data challenges, enabling timely, informed decisions.

What are the standout features of Palantir Gotham?

Data Integration: Connects various data sources for seamless data aggregation.
Analytical Models: Employs advanced analytics for comprehensive data insights.
Collaboration Tools: Facilitates team collaboration through shared data environments.

What benefits or ROI should users consider?

Enhanced Decision-Making: Provides actionable insights for informed decision-making.
Increased Efficiency: Streamlines operations and reduces processing time.
Scalability: Grows with organizational demands to maintain operational effectiveness.

In specific industries such as defense and finance, Palantir Gotham is used for threat intelligence and risk management, helping organizations mitigate threats and manage compliance efficiently. It's known for its adaptability in complex environments, making it a popular choice in sectors requiring rigorous data handling.

Palantir

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: October 2026.

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