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Palantir Foundry vs Qlik Compose comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 19, 2024

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

Palantir Foundry
Ranking in Data Integration
3rd
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
62
Ranking in other categories
IT Operations Analytics (4th), Supply Chain Analytics (1st), Cloud Data Integration (4th), Data Migration Appliances (2nd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
Qlik Compose
Ranking in Data Integration
52nd
Average Rating
7.6
Reviews Sentiment
6.5
Number of Reviews
12
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Palantir Foundry is 2.1%, down from 3.3% compared to the previous year. The mindshare of Qlik Compose is 0.8%, down from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Palantir Foundry2.1%
Qlik Compose0.8%
Other97.1%
Data Integration
 

Featured Reviews

reviewer2846265 - PeerSpot reviewer
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.
SA
Director - Metrics & Analytics at a computer software company with 1,001-5,000 employees
Efficient data warehouse automation with robust features, but may require enhancements in user-friendly self-service options and pricing flexibility for broader corporate appeal
It could enhance its capabilities in the realm of self-service options as currently, it is more suited for individuals with technical proficiency who can create pages using it. When it comes to end users who may lack technical expertise, they are limited to toggling between existing developments. To empower end users to make critical changes without relying heavily on technical expertise, it would be beneficial to introduce more user-friendly features for development and modification. If it could incorporate correlation analysis capabilities into its platform, especially in a user-friendly manner, it would greatly enhance the tool's overall utility and make it an even more outstanding solution. There is a room for improvement regarding stability.

Quotes from Members

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

Pros

"I like the data onboarding to Palantir Foundry and ETL creation."
"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."
"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."
"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."
"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."
"The best features Palantir Foundry offers include the semantic layer providing schema-level understanding about the data, low-code and no-code integration for ease without coding in the pipeline builder, AI Assist for assistance, Ontology for digital twin relationships, branching in pipeline level and Foundry branching for better management, zero-copy architecture for querying without massive data, data lineage for troubleshooting, and security changes that can be made in the pipeline builder and Ontology Workshop."
"From my experience with Palantir Foundry, the most useful feature is its no-code, low-code environment, allowing me to develop applications without extensive coding, unlike my past as an Oracle developer where I had to write code for various functions."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"There were many valuable features, such as extracting any data to put in the cloud. For example, Qlik was able to gather data from SAP and extract SAP data from the platforms."
"The technical support is very good. I rate the technical support a ten out of ten."
"I like modeling and code generation. It has become a pretty handy tool because of its short ideation to delivery time. From the time you decide you are modeling a data warehouse, and once you finish the modeling, it generates all the code, generates all the tables. All you have to do is tick a few things, and you can produce a fully functional warehouse. I also like that they have added all the features I have asked for over four years."
"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"I have found it to be a very good, stable, and strong product."
"It can scale."
"It is a scalable solution."
 

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."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"One challenge regarding how Palantir Foundry can be improved is the learning curve."
"The major hindrance with Palantir Foundry is that being a very closed product, the cost optimization and costing are not exposed to the end users."
"When we were using ETL with Palantir Foundry, we found we had less freedom compared to Cloudera, where we had more liberty in using various configuration parameters of Spark, allowing us to tune our jobs accordingly."
"The theme is very monotonous and should be improved."
"I cannot advise someone to use Palantir Foundry due to cost efficiency and the complexity it introduces in handling large amounts of data."
"Some error messages can be very cryptic."
"There could be more customization options."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"Qlik's ETL and data transformation could be better."
"When processing data from certain tables with a large volume of data, we encounter significant delays. For instance, when dealing with around one million records, it typically takes three to four hours. To address this, I aim to implement performance improvements across all tables, ensuring swift processing similar to those that are currently complete within seconds. The performance issue primarily arises when we analyze the inserts and updates from the source, subsequently dropping the table. While new insertions are handled promptly, updates are processed slowly, leading to performance issues. Despite consulting our Qlik vendors, they were unable to pinpoint the exact cause of this occurrence. Consequently, I am seeking ways to optimize performance within Qlik Compose, specifically concerning updates."
"The solution has room for improvement in the ETL. They have an ETL, but when it comes to the monitoring portion, Qlik Compose doesn't provide a feature for monitoring."
"I believe that visual data flow management and the transformation function should be improved."
"For more complex work, we are not using Qlik Compose because it cannot handle very high volumes at the moment. It needs the same batching capabilities that other ETL tools have. We can't batch the data into small chunks when transforming large amounts of data. It tries to do everything in one shot and that's where it fails."
"It would be better if the first level of technical support were a bit more technically knowledgeable to solve the problem. I think they could also improve the injection of custom scripts. It is pretty difficult to add additional scripts. If the modeling doesn't give you what you want, and you want to change the script generated by the modeling, it is a bit more challenging than in most other products. It is very good with standard form type systems, but if you get a more complicated data paradigm, it tends to struggle with transforming that into a model."
 

Pricing and Cost Advice

"The solution’s pricing is high."
"It's expensive."
"Palantir Foundry is an expensive solution."
"Palantir Foundry has different pricing models that can be negotiated."
"While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us."
"The price of the solution is expensive."
"On a scale of one to ten, where one is cheap, and ten is very expensive, I rate the solution a six."
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Top Industries

By visitors reading reviews
Manufacturing Company
14%
Financial Services Firm
10%
Government
7%
Healthcare Company
6%
Financial Services Firm
13%
Comms Service Provider
10%
Construction Company
10%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise7
Large Enterprise50
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise3
Large Enterprise6
 

Questions from the Community

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 ...
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 ...
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...
Which ETL tool would you recommend to populate data from OLTP to OLAP?
There are two products I know about * TimeXtender : Microsoft based, Transformation logic is quiet good and can easily be extended with T-SQL , Has a semantic layer that generates metat data for cu...
 

Also Known As

No data available
Compose, Attunity Compose
 

Overview

 

Sample Customers

Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Poly-Wood
Find out what your peers are saying about Palantir Foundry vs. Qlik Compose and other solutions. Updated: August 2026.
909,153 professionals have used our research since 2012.