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 8.0, while Palantir is ranked #1 with an average rating of 8.2. Fabric Data holds a 0.8% mindshare in DaAS, compared to Palantir’s 8.4% 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

631 Views
625 Comparison Views

95% willing to recommend

Palantir Foundry

Read 62 Palantir Foundry reviews

15,651 Views
2,348 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: August 2026).

Buyer's Guide

Fabric Data vs. Palantir Foundry

August 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

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 (3rd), 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 August 2026, in the Data and Analytics Service Providers category, the mindshare of Fabric Data is 0.8%, up from 0.5% compared to the previous year. The mindshare of Palantir Foundry is 8.4%, down from 11.0% 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	8.4%
Fabric Data	0.8%
Other	90.8%

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.

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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

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

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

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

"Fabric Data has allowed us to change that and put the entire solution in one package and one environment, and that also makes things much more stable."

"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."

"The unified workspace is the biggest advantage I experienced while building those data pipelines and working with OneLake storage."

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

"Previously, we were using Databricks for this, but we switched to Fabric Data because Fabric Data is more integrated, we don't need to shift our data from one tool to another, and all the processing and visualization can be done inside Microsoft Fabric Data."

More Fabric Data pros

"Palantir Foundry has positively impacted my organization by increasing the operational throughput of the yard, which focuses on building new ships or repairing existing ones."

"Palantir Foundry positively impacts our organization by being seamlessly integrated and offering easy-to-access features without the need for third-party integrations, with everything already in place benefiting developers and subsequently enhancing managers' productivity, leading to overall organizational revenue growth."

"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."

"The predictive analytics capability within Palantir Foundry impacts financial forecasting strategies through its AIP functionality, which includes numerous pre-built models, LLMs, and data science application libraries."

"Palantir Foundry has dramatically helped us in terms of project costing because earlier we had our own React developers team from offshore, and now with the AIP capabilities launched on the platform, we have completely avoided the need for a dedicated team, which has been very helpful in terms of cost management and reducing team size."

"Palantir Foundry has proven to be a great tool in terms of scalability for me, especially compared to Power BI, which felt inadequate, as its scalability depends on the Slate application and I am only limited by my imagination."

"It's scalable."

"Palantir Foundry has positively impacted my organization mainly by consolidating our data management, so we do not need multiple accounts for different applications and can keep all our data within Palantir Foundry while accessing all applications from there without moving data between locations."

More Palantir Foundry pros

Cons

"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."

"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."

"To improve Fabric Data, I suggest more integration with additional data sources and better integration for data agents."

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

"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."

"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."

"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."

More Fabric Data cons

"It is a very complicated platform, and you need to understand a lot about how to use it and the underlying thinking behind Foundry."

"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."

"Palantir Foundry could be improved by addressing the need for some coding in the Workshop since we cannot expect 100% no-code functionality, especially when dealing with dynamic user input, which requires writing functions in the Code Repository."

"I would add that live data streaming is very hard and it keeps breaking, so it is not very stable and depends a lot on the satellite network."

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

"I think much of the work within Palantir Foundry is still manual, so I might want to write certain automations or develop conversational interfaces rapidly."

"The data lineage was challenging. It's hard to track data from the sources as it moves through stages. Informatica EDC can easily capture and report it because it talks to the metadata. This is generated across those various staging points."

"Palantir Foundry has a steep learning curve and onboarding."

More Palantir Foundry cons

Pricing and Cost Advice

Information not available

"The solution’s pricing is high."

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

"It's expensive."

"Palantir Foundry is an expensive solution."

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Top Industries

By visitors reading reviews

Manufacturing Company

17%

Financial Services Firm

15%

University

13%

Healthcare Company

Manufacturing Company

14%

Financial Services Firm

10%

Government

Healthcare Company

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	50

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 ...

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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...

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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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Product Reports

Buyer's Guide

Fabric Data

August 2026

Download Fabric Data product report

Buyer's Guide

Palantir Foundry

August 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

August 2026

Free Report: Fabric Data vs. Palantir Foundry

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