Fabric Data vs Palantir Foundry comparison

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 7.9, while Palantir is ranked #1 with an average rating of 8.3. Fabric Data holds a 0.7% mindshare in DaAS, compared to Palantir’s 7.6% mindshare. Additionally, 95% of Fabric Data users are willing to recommend the solution, compared to 91% of Palantir users who would recommend it.

Fabric Data

Read 20 Fabric Data reviews

452 Views
443 Comparison Views

95% willing to recommend

Palantir Foundry

Read 47 Palantir Foundry reviews

13,191 Views
1,847 Comparison Views

91% 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: May 2026).

Buyer's Guide

Fabric Data vs. Palantir Foundry

May 2026

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Helped 896,942 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

6.5

Number of Reviews

Ranking in other categories

Data Integration (5th), IT Operations Analytics (5th), Supply Chain Analytics (1st), Cloud Data Integration (4th), Data Migration Appliances (2nd), Data Management Platforms (DMP) (1st)

Mindshare comparison

As of June 2026, in the Data and Analytics Service Providers category, the mindshare of Fabric Data is 0.7%, up from 0.7% compared to the previous year. The mindshare of Palantir Foundry is 7.6%, down from 13.0% 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	7.6%
Fabric Data	0.7%
Other	91.7%

Data and Analytics Service Providers

Featured Reviews

Pranav Vighe

Data Engineer at IRT Dogotal ANlytics

Automation of complex data workflows has reduced processing time and improves project delivery

The best features Fabric Data offers include Fabric Data Shortcut as the main feature, and also the integration of all the components like ingestion, transformation notebooks, and the deployment pipeline for CI/CD, which are game-changing. The visualization features are also great, and the features Fabric Data offers are different. The feature I find myself using the most is the time travel feature because I mainly work with data transformation. Whenever bad updates happen, I use the time travel feature the most. There is a high concurrency feature that can be applied in pipelines; we just need to add the high concurrency tag, and the pipeline will not start a new cluster each time the notebook runs. Fabric Data will use the same cluster for the notebook run, and this feature is a game-changer. Fabric Data positively impacts my organization by bringing us more projects and work to do and also reduces the time significantly. Nearly 20 to 30 hours per week were reduced by using Fabric Data, and it is also very cost-optimized.

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 offers the best features by delivering a well-integrated, modern data engineering experience as a learning and certification platform."

"What I appreciate about Fabric Data is that it is easy to use and user-friendly, and additionally, it is cost-efficient."

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

"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."

"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."

"The best features are that the entire ecosystem is inside Microsoft and it is under a SaaS platform."

"Fabric Data has impacted my organization positively because collaboration has been better and deployments have been faster."

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

More Fabric Data pros

"Palantir Foundry has positively impacted my organization through multiple use cases, such as warranty data refinement, where previously we struggled with identifying the number of claims related to specific products."

"Palantir Foundry has positively impacted my organization by providing good support from Palantir teams, facilitating the development of many new solutions, building our UI and web applications, and significantly enhancing our productivity."

"Palantir Foundry has reduced a very good amount of time to implement a data pipeline and process the data within four hours."

"Compared to other SaaS tools, Palantir Foundry is definitely a time-saver, though I do not have specific metrics to share."

"Palantir Foundry gives me a unified view of AI and my engineering space while I have been doing a lot of data engineering in a couple of technologies, bringing that data together and stitching them and putting together AI, enabling AI use cases, which makes me see a holistic view of data coming from various platforms."

"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."

"Palantir Foundry is one of the most leading and comfortable tools to develop end-to-end data solutions."

"Palantir Foundry has positively impacted my organization by centralizing the way we build applications and standardizing business metric reporting, creating more alignment across my team and the organization, greater productivity between teams, and quicker cycle times into production."

More Palantir Foundry pros

Cons

"There needs to be improvement in error handling and resource management because some of the documentation is not clear."

"I believe Excel sheets have some issues when creating a data frame; however, JSON data works fine for Fabric Data. When using an Excel sheet, we need some extra libraries, and that feature would be useful because most e-commerce sites store data in Excel."

"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."

"The inability to monitor properly and having to build in fail conditions in pipelines, or navigate around it, was so painful that it is borderline unuseful for any large company in a production environment, and that would be at the top of my list."

"Fabric Data can be improved because it tends to be run by Fabric Capacity, which is basically the compute cycles, and it is not very clear on how and what that is going to be used."

"One thing regarding needed improvements is related to the free tier or trial capacity. When I was learning Microsoft Azure services, it was very easy to get credits and a free account, but in Fabric, it was inconvenient to get a free tier or trial capacity."

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

"I felt some features of Fabric Data, particularly around Dataflow Gen2 error handling and pipeline monitoring, lack clear documentation at the time of my study."

More Fabric Data cons

"Regarding pricing, I heard about it, and until last year, the license was one million dollars. They have now increased this to four million dollars, which is high."

"The solution could use more online documentation for new users."

"Palantir Foundry's stability is sometimes good and sometimes not; there are blunders and issues."

"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."

"Cost of this solution is quite high."

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

"The widgets are pretty limited."

"There are some issues with scalability because when we are using a really large dataset, the system is rather slow."

More Palantir Foundry cons

Pricing and Cost Advice

Information not available

"Palantir Foundry is an expensive solution."

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

"It's expensive."

"The solution’s pricing is high."

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Top Industries

By visitors reading reviews

Manufacturing Company

18%

Financial Services Firm

16%

University

15%

Healthcare Company

Manufacturing Company

13%

Financial Services Firm

Government

University

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	38

Questions from the Community

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

My experience with pricing, setup cost, and licensing involves having a student trial.

See all answers

What needs improvement with Fabric Data?

The improvement part I foresee for Fabric Data is going to be with the AI. Copilot in Power BI feels weak compared to standalone third-party assistants. Microsoft has the platform advantage but the...

See all answers

What is your primary use case for Fabric Data?

I have been using Fabric Data for the past two years. My main use case for Fabric Data is building pipelines with notebooks and then surfacing the output in Power BI. Doing the data engineering ins...

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What needs improvement with Palantir Foundry?

Regarding points for improvement for Palantir Foundry, I see that they are improving day by day. In the last one to two years, I have seen many improvements compared to the two years that I have wo...

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What is your primary use case for Palantir Foundry?

There are several use cases that we are working on with Palantir Foundry. The first thing is for data model creation for all our data engineering pipelines. That is one use case. Palantir Foundry a...

See all answers

What advice do you have for others considering Palantir Foundry?

The visualization part in Palantir Foundry works for me at least if I want to see how the data is structured and for an initial analysis, but I would say it is not as matured as Power BI or Tableau...

See all answers

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Product Reports

Buyer's Guide

Fabric Data

May 2026

Download Fabric Data product report

Buyer's Guide

Palantir Foundry

May 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

May 2026

Free Report: Fabric Data vs. Palantir Foundry

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