Fabric Data vs Palantir Foundry comparison

Why PeerSpot?

Fabric Data and Palantir are both solutions in the Data and Analytics Service Providers category. Fabric Data is ranked #3 with an average rating of 8.0, while Palantir is ranked #1 with an average rating of 8.2. Fabric Data holds a 1.0% mindshare in DaAS, compared to Palantir’s 9.9% mindshare. Additionally, 95% of Fabric Data users are willing to recommend the solution, compared to 93% of Palantir users who would recommend it.

Fabric Data

Read 21 Fabric Data reviews

904 Views
895 Comparison Views

95% willing to recommend

Palantir Foundry

Read 62 Palantir Foundry reviews

18,809 Views
3,009 Comparison Views

93% willing to recommend

Fabric Data

Palantir Foundry

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Fabric Data and Palantir Foundry based on real PeerSpot user reviews.

Find out in this report how the two Data and Analytics Service Providers solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Fabric Data vs. Palantir Foundry Report (Updated: September 2026).

Buyer's Guide

Fabric Data vs. Palantir Foundry

September 2026

Download the complete report

Helped 917,433 peers since 2012

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

Fabric Data

Ranking in Data and Analytics Service Providers

3rd

Average Rating

8.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Palantir Foundry

Ranking in Data and Analytics Service Providers

1st

Average Rating

8.0

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Integration (2nd), IT Operations Analytics (4th), Supply Chain Analytics (1st), Cloud Data Integration (4th), Data Migration Appliances (2nd), Data Management Platforms (DMP) (1st)

Mindshare comparison

As of October 2026, in the Data and Analytics Service Providers category, the mindshare of Fabric Data is 1.0%, up from 0.5% compared to the previous year. The mindshare of Palantir Foundry is 9.9%, down from 10.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data and Analytics Service Providers Mindshare Distribution
Product	Mindshare (%)
Palantir Foundry	9.9%
Fabric Data	1.0%
Other	89.1%

Data and Analytics Service Providers

Featured Reviews

Xin Wen

Student at Northeastern University

Unified data workflows have simplified certification prep and improved hands-on analytics practice

The unified workspace is the biggest advantage I experienced while building those data pipelines and working with OneLake storage. Having data ingestion, transformation, storage, and reporting all within one platform significantly reduces the complexity of switching between tools. The integration with the broader Microsoft ecosystem felt natural, especially for someone who is already familiar with Azure services. The Microsoft Learn documentation and sandbox environments made it accessible for structured self-study. Fabric Data's strongest aspect positively impacts my organization and my work with its native integration across the Microsoft data stack. OneLake serves as a single unified storage layer across all Fabric Data workloads, meaning data written by a pipeline is immediately accessible in Lakehouse, Warehouse, and Power BI without duplication or manual transfer. This eliminates the data silo problem that commonly affects multi-tool environments. Dataflow Gen2 uses the familiar Power Query interface, making it accessible to analysts already working in Excel or Power BI. The output of a dataflow can be directly directed into a Lakehouse table, which then becomes queryable via the SQL analytics endpoint without additional configuration, significantly impacting my workflow.

Read full review

reviewer2846265

PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees

Unified healthcare pipelines have improved data trust and accelerated operational decisions

One challenge regarding how Palantir Foundry can be improved is the learning curve. Foundry has a very broad ecosystem with Ontology, Pipeline Builder, Code Repositories, and AI integrations. For new engineers or business users onboarding, it can take time, especially if they are coming from more traditional data platforms. Better documentation, simplified onboarding paths, and more beginner-friendly examples would help accelerate adoption. Another area is debugging complexity. While lineage and monitoring are strong features, troubleshooting deeply interconnected pipelines can still become difficult in a large enterprise environment. Sometimes error logs and pipeline failure messages could be more descriptive or developer-friendly, especially for distributed PySpark jobs. Another pain point is customization limitations in certain UI-driven components. While low-code tools are great for rapid development, highly customized workflows sometimes still require engineering workarounds or deeper technical implementation. The platform is extremely capable, but improvements around usability, debugging experience, DevOps flexibility, and ecosystem openness would make it even more effective for enterprise engineering teams.

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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

"Fabric Data is very useful for our organization and our clients as well, saving time, simplicity, and offering many benefits."

"I enjoy working with the pipelines since they provide a full end-to-end use case for me to take the data and report everything in one place instead of going back and forth with databases and engineers, allowing me to feel as a data scientist, data engineer, and business analyst in one location, giving me full authority to control everything."

"The best features Fabric Data offers are its versatility, as you can use data fabric for many uses in one single platform."

"We have certainly saved a significant amount of time by switching from small-scale tools to Fabric Data, which has improved visibility and increased accuracy."

"Fabric Data has positively impacted my organization by providing a unified platform for the entire data for the customer which we are working on."

"I have seen a return on investment that is highly notable; the solutions I am getting from transitioning traditional ETL solutions to Fabric Data are remarkable."

"Fabric Data enables me to get the data from multiple resources, whether on-premises or any other Azure service providers, and also allows me to transfer and migrate the data from any other platform to Fabric Data smoothly."

"Fabric Data has positively impacted my organization as my company is a consultant company and we have implemented these projects for our clients."

More Fabric Data pros

"In my experience, the best features Palantir Foundry offers are its usefulness for all levels of people from analysts to product managers to software engineers."

"Palantir Foundry's AI capabilities, governance, and security are top tier as it is a fully locked environment and is best for government organizations where data security is a major consideration."

"The data lineage is great."

"Palantir Foundry is not just a data platform; it actually connects data engineering, analytics, operations, and decision-making all into one ecosystem."

"I appreciate multiple aspects of Palantir Foundry, starting with the clean architecture and clean UI, and I really value how easily I can create and test Python and PySpark scripts, trace data lineage to debug issues, monitor daily pipelines and health checks, and quickly build very interactive Workshop applications, all supported by a clean and informative Resource Management UI that helps track costs and data usage."

"The scalability of Palantir Foundry is the part that I love the most."

"Palantir Foundry has improved with the generation of AI, and I think the governance and security are both good things to have in Palantir Foundry."

"Great features available in one tool."

More Palantir Foundry pros

Cons

"One area Fabric Data can be improved is the semantic model refresh. Though it says it is a direct link, the refresh times of the semantic model sometimes need explicit refresh."

"I think Fabric Data could be improved by adding more notebooks, even though it currently has one."

"Customer support receives a rating of six out of ten because they themselves are trying to figure out what is new and what the issue is."

"Fabric Data could be improved in the future by increasing the size capability from terabyte to petabyte for deeper integration."

"Speed is a factor which Fabric Data says and confirms they will improve. The data speed will improve, but it is not a significant improvement as per the capability of Fabric Data."

"I feel that the Copilot in Power BI is very weak; for example, if you power it with the cloud, it is much more powerful than the Copilot in Power BI, which I believe could offer much better insights since it is a Microsoft tool."

"The main improvement I would like to see is more integration with other tools; for example, SAP integration should be there because there are more integration tools available in Azure Data Factory than in Fabric Data, and I would like to have more integrations in Fabric Data."

"One area is performance optimization and monitoring visibility for large-scale workloads."

More Fabric Data cons

"However, a disadvantage is the challenge of connecting data to and from Palantir, which requires coordination with data engineers."

"The workflow could be improved."

"The theme is very monotonous and should be improved."

"The one area where improvement could be made is the cost of the solution which is quite expensive."

"Always having to work with a Palantir representative creates severe bottlenecks and increases costs, making it desirable for me as the end user to perform tasks without constant requests for support."

"In my use of Palantir Foundry, many people can go in there and create datasets, save datasets, and share datasets. However, if many people make datasets of low quality or if they are using the same name for datasets, it can get very confusing."

"However, Palantir Foundry's license fees comparative to others are quite high."

"As a developer, I find the limited documentation and less resource availability restrictive compared to other options such as AWS."

More Palantir Foundry cons

Pricing and Cost Advice

Information not available

"Palantir Foundry has different pricing models that can be negotiated."

"Palantir Foundry is an expensive solution."

"The solution’s pricing is high."

"It's expensive."

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Top Industries

By visitors reading reviews

Manufacturing Company

16%

Financial Services Firm

13%

University

11%

Outsourcing Company

Manufacturing Company

15%

Financial Services Firm

10%

Comms Service Provider

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	2
Large Enterprise	16

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	7
Large Enterprise	51

Questions from the Community

What is your experience regarding pricing and costs for Fabric Data?

My experience with pricing, setup cost, and licensing is that pricing and those aspects are a different matter. It is not a concern for me because it matters to the client. Compared to other option...

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What needs improvement with Fabric Data?

One area Fabric Data can be improved is the semantic model refresh. Though it says it is a direct link, the refresh times of the semantic model sometimes need explicit refresh. This takes a bit of ...

See all answers

What is your primary use case for Fabric Data?

My main use case for Fabric Data is building data solutions for one of the retail firms in the US. I use Fabric to process source data, perform data processing, and provide analytical reports for e...

See all answers

What needs improvement with Palantir Foundry?

The Workshop application could be improved because it is not very customizable, but it is still very strong. We also have the React OSK apps, but it does not allow the inbuilt applications such as ...

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What is your primary use case for Palantir Foundry?

My main use case for Palantir Foundry is to solve business problems, such as in healthcare. I also worked on a project for a law firm where thousands of PDFs were coming in, and we needed to check ...

See all answers

What advice do you have for others considering Palantir Foundry?

I believe they should get started by completing all the free certificates, then they could apply to the paid certificates to get a master of Palantir Foundry, solve some real use cases, do examples...

See all answers

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Compared 3% of the time

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Product Reports

Buyer's Guide

Fabric Data

October 2026

Download Fabric Data product report

Buyer's Guide

Palantir Foundry

October 2026

Download Palantir Foundry product report

Overview

Fabric Data delivers powerful data management to streamline analytics, enhance data accessibility, and improve business decision-making processes within enterprises.

Fabric Data is designed to address complex data environments, offering a comprehensive approach to ensuring data integrity and consistency. Targeted towards data-driven organizations, it simplifies data management and integration, making data easy to access and utilize for advanced analytics and reporting. By facilitating seamless scalability, it supports growth and evolving data requirements efficiently.

What are the most important features of Fabric Data?

Data Integration: Simplifies the merging of multiple data sources into a single cohesive system.
Scalability: Adaptable framework allows for effortless expansion as needs grow.
Data Security: Implements robust measures to protect sensitive information.
Real-time Analytics: Offers immediate insights for faster decision-making.

What benefits or ROI should users look for in reviews?

Improved Efficiency: Streamlines data processes, reducing time and effort.
Cost Savings: Lowers operational costs by automating tasks and enhancing productivity.
Enhanced Decision-making: Provides reliable data insights to inform strategy.
Increased Agility: Respond quickly to changes with flexible data management.

Fabric Data can be implemented in sectors such as finance, healthcare, and retail, where it facilitates data-driven strategies, enhances customer experiences, and optimizes operational efficiencies. In finance, it supports risk management and regulatory compliance. In healthcare, it contributes to patient data management and care personalization.

Fabric Data

Palantir Foundry offers intuitive data management and application development, prioritizing accessibility through low-code/no-code tools, enabling users to integrate, analyze, and collaborate efficiently.

Palantir Foundry centers on user accessibility, data governance, and real-time capabilities, streamlining processes with low-code/no-code development. It supports comprehensive data analysis and integration, enhanced by digital twin features that align virtual and physical interactions. Despite high costs and performance challenges with large datasets, it remains a prime choice for sectors needing structured and unstructured data integration. Key areas include robust data security, lineage tracking, and predictive analytics, promoted through a unified management platform adaptable to diverse needs.

What are the key features of Palantir Foundry?

User-friendly interface enabling easy data governance and automation.
Real-time integration with strong data analysis and collaboration tools.
Low-code/no-code development to widen accessibility.
Digital twin capabilities for bi-directional process integration.
Strong data lineage, predictive analytics, and visualization tools.
Flexibility and customization options.

What benefits and ROI could reviews highlight?

Improved decision-making through enhanced data visibility.
Increased efficiency with automated data processes.
Broader accessibility to data insights via low-code options.
Enhanced collaboration and integration between departments.
Potential cost savings through streamlined operations.

In manufacturing, Palantir Foundry aids in engineering pipeline models and semantic frameworks, while utilities utilize its analytics to enhance service delivery. Insurance firms leverage its capability to assess and predict customer behavior. Throughout these industries, Foundry integrates across cloud environments, bridging structured and unstructured data from various sources.

Palantir

Sample Customers

Information Not Available

Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense

Buyer's Guide

Fabric Data vs. Palantir Foundry

September 2026

Free Report: Fabric Data vs. Palantir Foundry

Find out what your peers are saying about Fabric Data vs. Palantir Foundry and other solutions. Updated: September 2026.

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