Palantir Foundry vs Qlik Compose comparison

Why PeerSpot?

Palantir and Qlik are both solutions in the Data Integration category. Palantir is ranked #3 with an average rating of 8.2, while Qlik is ranked #58. Palantir holds a 2.2% mindshare in DI, compared to Qlik’s 0.8% mindshare. Additionally, 93% of Palantir users are willing to recommend the solution, compared to 81% of Qlik users who would recommend it.

Palantir Foundry

Read 62 Palantir Foundry reviews

20,123 Views
8,250 Comparison Views

93% willing to recommend

Qlik Compose

Read 12 Qlik Compose reviews

3,286 Views
2,563 Comparison Views

81% willing to recommend

Palantir Foundry

Qlik Compose

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 19, 2024

Qlik Compose and Palantir Foundry are products competing in data management and analytics. Palantir Foundry has the upper hand due to its advanced features and perceived value, despite Qlik Compose's favorable pricing and support.

Features: Qlik Compose focuses on data automation, robust ETL processes, and ease of data integration. It offers an intuitive and user-friendly interface and facilitates data modeling and code generation. Palantir Foundry excels in comprehensive data analytics and integration, seamless collaboration, and superior data visualization. It provides powerful data lineage tracing and a robust end-to-end tech stack.

Room for Improvement: Qlik Compose can enhance its data integration capabilities, real-time data handling, and offer more advanced data analytics features. It could improve support for non-traditional data sources and enhance its user interface to accommodate a broader range of users. Palantir Foundry could further simplify its deployment process, reduce overall costs, and improve customer support to be more accessible and responsive. It may also look into making its features more intuitively accessible for non-technical users.

Ease of Deployment and Customer Service: Palantir Foundry offers versatile cloud-based deployment for customization but can be complex. Its innovative customer service approach helps address unique client needs. Qlik Compose provides a straightforward on-premise setup, with traditional yet reliable customer support mechanisms.

Pricing and ROI: Qlik Compose is recognized for its cost-effective setup and scalable pricing strategy, promising a good ROI. Palantir Foundry, though more costly, justifies its price with advanced features and scalability, offering significant long-term ROI advantages. The choice depends on whether affordability or feature richness is prioritized.

To learn more, read our detailed Palantir Foundry vs. Qlik Compose Report (Updated: October 2026).

Buyer's Guide

Palantir Foundry vs. Qlik Compose

October 2026

Download the complete report

Helped 921,523 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

Palantir Foundry

Ranking in Data Integration

3rd

Average Rating

8.0

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

IT Operations Analytics (4th), Supply Chain Analytics (1st), Cloud Data Integration (5th), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)

Qlik Compose

Ranking in Data Integration

58th

Average Rating

7.6

Reviews Sentiment

6.5

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 Palantir Foundry is 2.2%, down from 2.7% compared to the previous year. The mindshare of Qlik Compose is 0.8%, down from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Palantir Foundry	2.2%
Qlik Compose	0.8%
Other	97.0%

Data Integration

Featured Reviews

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.

Read full review

Susheel A

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.

Read full review

Quotes from Members

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

Pros

"From my experience, one of the best features Palantir Foundry offers is that you have everything in one ecosystem."

"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 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."

"Based on my huge experience with Palantir Foundry, I find that starting from the data connection to the end user application, there is a tool for everyone."

"Palantir Foundry has positively impacted my organization, as we are dependent on Palantir Foundry for processing the data."

"The AI engine that comes with Palantir Foundry is quite interesting."

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

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

More Palantir Foundry pros

"I have found it to be a very good, stable, and strong product."

"The technical support is very good. I rate the technical support a ten out of ten."

"It is a scalable solution."

"One of the most valuable features of this tool is its automation capabilities, allowing us to design the warehouse in an automated manner. Additionally, we can generate Data Lifecycle Policies (DLP) reports and efficiently implement updates and best practices based on proven design patterns."

"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."

"It can scale."

"The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities."

"As long as you pick the solution that best fits with your requirements, you won't find that performance is a problem. It's good."

More Qlik Compose pros

Cons

"The solution's visualization and analysis could be improved."

"For example, exporting data from Palantir Foundry is very difficult and has many limitations."

"I choose eight out of ten because the software still needs a lot of updates to make it stable, and today, it is not stable."

"The frontend capabilities of Palantir Foundry could be improved."

"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."

"Sometimes it takes time to refresh the UI, especially since it is cloud-based."

"If it was my choice, I wouldn't sign the contract with Palantir in the first place. I would probably stick to standard Databricks."

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

More Palantir Foundry cons

"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 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."

"My issues with the solution's stability are owing to the fact that it has certain bugs causing issues in some functionalities that should be working."

"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."

"There is some scope for improvement around the documentation, and a better UI would definitely help."

"There should be proper documentation available for the implementation process."

"I don't think Qlik can be used in a high-volume scenario. It didn't work for us."

More Qlik Compose cons

Pricing and Cost Advice

"The solution’s pricing is high."

"Palantir Foundry is an expensive solution."

"It's expensive."

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

"On a scale of one to ten, where one is cheap, and ten is very expensive, I rate the solution a six."

"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."

See which vendors are best for you

Use our free recommendation engine to learn which Data Integration solutions are best for your needs.

See recommendations

921,523 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Manufacturing Company

14%

Financial Services Firm

10%

Comms Service Provider

Outsourcing Company

Financial Services Firm

12%

Comms Service Provider

10%

Construction Company

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	3
Large Enterprise	6

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 ...

See all answers

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

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...

See all answers

Comparisons

Accenture AI services vs Palantir Foundry

Compared 6% of the time

Databricks vs Palantir Foundry

Compared 4% of the time

Cognizant AI & Analytics vs Palantir Foundry

Compared 3% of the time

Palantir Gotham vs Palantir Foundry

Compared 3% of the time

Splunk Enterprise Security vs Palantir Foundry

Compared 3% of the time

More Palantir Foundry Competitors

AWS Database Migration Service vs Qlik Compose

Compared 9% of the time

Qlik Replicate vs Qlik Compose

Compared 7% of the time

SSIS vs Qlik Compose

Compared 6% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Qlik Compose

Compared 6% of the time

FME vs Qlik Compose

Compared 3% of the time

More Qlik Compose Competitors

Product Reports

Buyer's Guide

Palantir Foundry

October 2026

Download Palantir Foundry product report

Buyer's Guide

Qlik Compose

October 2026

Download Qlik Compose product report

Also Known As

No data available

Compose, Attunity Compose

Overview

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

Qlik Compose enhances data management with ETL capabilities, data integration with CDC, and real-time replication. Its intuitive interface enables easy data modeling and automation, supporting various database integrations.

Qlik Compose is designed for efficient data preparation, migration, and warehouse generation. It incorporates ETL functionalities and data integration with CDC, allowing users to effortlessly create data marts without code. Its automation features facilitate warehouse design while graphical representations and connectivity options increase versatility across multiple sources. Users value its stability, scalability, and the support provided, although improvements in ETL functionalities, performance for large datasets, and NoSQL integration are needed. The solution is widely used in business intelligence with tools like Qlik Replicate for real-time data replication and requires direct SQL for complex transformations.

What are the key features of Qlik Compose?

ETL Capabilities: Simplifies data extraction, transformation, and loading
Data Integration with CDC: Enables real-time data replication
Intuitive Interface: Facilitates easy data modeling and automation
Drag-and-Drop Functionality: Streamlines data task management
Auto-Mapping: Enhances integration of multiple data sources
No-Code Data Marts Creation: Reduces dependency on technical skills

What benefits should users consider in the reviews?

Stability and Scalability: Reliable functioning for growing data needs
Technical Support: Availability of assistance for troubleshooting
Real-Time Replication Capabilities: Efficient data processing and analytics
Low-Code Development: Simplifies complex data handling processes

In industries, Qlik Compose is implemented for enhancing data preparation, migration, and warehousing. It is used in small projects or straightforward data integration tasks and supports business intelligence efforts by offering low-code capabilities, enabling companies to deliver tailored analytics solutions efficiently.

Qlik

Sample Customers

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

Poly-Wood

Buyer's Guide

Palantir Foundry vs. Qlik Compose

October 2026

Free Report: Palantir Foundry vs. Qlik Compose

Find out what your peers are saying about Palantir Foundry vs. Qlik Compose and other solutions. Updated: October 2026.

DOWNLOAD NOW

921,523 professionals have used our research since 2012.

See our Palantir Foundry vs. Qlik Compose report.

See our list of best Data Integration vendors and best Cloud Data Integration vendors.

We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.