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Palantir Foundry vs erwin Data Catalog comparison

 

Comparison Buyer's Guide

Executive Summary

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

erwin Data Catalog
Average Rating
7.6
Reviews Sentiment
5.1
Number of Reviews
2
Ranking in other categories
Metadata Management (13th)
Palantir Foundry
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
59
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), Data and Analytics Service Providers (1st)
 

Mindshare comparison

erwin Data Catalog and Palantir Foundry aren’t in the same category and serve different purposes. erwin Data Catalog is designed for Metadata Management and holds a mindshare of 3.1%, up 2.3% compared to last year.
Palantir Foundry, on the other hand, focuses on Data Integration, holds 2.0% mindshare, down 3.0% since last year.
Metadata Management Mindshare Distribution
ProductMindshare (%)
erwin Data Catalog3.1%
Collibra Platform16.4%
Informatica Intelligent Data Management Cloud (IDMC)13.2%
Other67.3%
Metadata Management
Data Integration Mindshare Distribution
ProductMindshare (%)
Palantir Foundry2.0%
Informatica Intelligent Data Management Cloud (IDMC)3.7%
SSIS3.6%
Other90.7%
Data Integration
 

Featured Reviews

Andres-Martinez - PeerSpot reviewer
BI Data Analytics Engineer at Targa Research
Helps with metadata management, saves time, and allows us to do impact analysis on any changes
There are always ways to improve things. For example, we can use AI to be able to find out something. When we are typing something, if we don't know the exact term, Artificial Intelligence would be useful to find terms that are phonetically or syntactically similar. Instead of having to type in the exact name, they can provide those in the list. So, they can provide AI support for the search because when you have thousands and thousands of terms, it is hard to remember all the names. There were some issues when drawing the data models. If you have more than 500 or 600 tables, it takes a long time to display those in the right position on the screen. That can also be improved. They need some caching and some parallel pipelines working on the backend in order to divide it into sections.
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.

Quotes from Members

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

Pros

"The data catalog feature is pretty good."
"When you combine it with data lineage, every time you need to make a change, it allows you to do impact analysis on any changes and then connect to the end-users or data stewards so that they can be aware that a change is coming. That's one of the main benefits we use it for."
"Foundry's data visualization is fantastic."
"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 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."
"Based on my experience, Palantir Foundry is extremely easy to learn and adjust to since it is primarily a closed system, meaning that all the functions for data ingestion, data cleaning, machine learning, and related tasks can be performed from within the same system."
"The interface is really user-friendly."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"The security is also excellent. It's highly granular, so the admins have a high degree of control, and there are many levels of security. That worked well. You won't have an EDC unless you put everything onto the platform because it is its own isolated thing."
"The best features Palantir Foundry offers are the ease of use and the availability of all the different functionalities in a single space, making it a very convenient application to use for varying different purposes such as the workflow I mentioned."
 

Cons

"There are always ways to improve things. For example, we can use AI to be able to find out something. When we are typing something, if we don't know the exact term, Artificial Intelligence would be useful to find terms that are phonetically or syntactically similar. Instead of having to type in the exact name, they can provide those in the list. So, they can provide AI support for the search because when you have thousands and thousands of terms, it is hard to remember all the names."
"There were some issues when drawing the data models. If you have more than 500 or 600 tables, it takes a long time to display those in the right position on the screen."
"There is room for improvement with respect to the connector and how to connect to the structured and unstructured database."
"Palantir Foundry needs more resources to understand and train new, incoming resources to understand the basic knowledge of the entire platform."
"The problem is that interaction with outside applications can be difficult with the current setup that Palantir Foundry has."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"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."
"I want to say that Palantir Foundry is quite expensive; it is not so easy for budget review and budget transformation of the company, which is quite expensive."
"As a developer, I find the limited documentation and less resource availability restrictive compared to other options such as AWS."
"Regarding documentation, I find that when I face issues, the outdated documentation is not helpful; for example, while trying to create a webhook to fetch SharePoint metadata, I found available resources lacking relevance, needing significant updates to assist users properly."
"I believe that the AI or agent needs improvement because sometimes we face difficulties when looking for solutions, and when we ask the agent, AIP, it does not understand our queries and occasionally provides wrong solutions."
 

Pricing and Cost Advice

"Erwin Data Catalog is very expensive."
"I am not very familiar with its pricing. I know it is not cheap, but it is also not super expensive. It depends on the company size. For a company making $1 million, it is very expensive. For a company making 10 million and above, it might be okay."
"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."
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Top Industries

By visitors reading reviews
Construction Company
15%
Financial Services Firm
13%
Manufacturing Company
8%
Government
7%
Manufacturing Company
14%
Financial Services Firm
9%
Government
7%
University
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise7
Large Enterprise49
 

Questions from the Community

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...
What needs improvement with Palantir Foundry?
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 n...
What is your primary use case for Palantir Foundry?
I use Palantir Foundry for my primary use case, which involves building and maintaining end-to-end pipelines and operational data products at UHG for our healthcare analytics team. I work on data i...
What advice do you have for others considering Palantir Foundry?
My advice would be to approach Palantir Foundry as an enterprise operational platform, not just a traditional data tool. The platform delivers the most value when organizations fully leverage its g...
 

Overview

 

Sample Customers

Balfour Beatty Construction, Banco de México, BFSI Canada, CenturyLink, Daktronics
Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Find out what your peers are saying about Collibra, Informatica, Alation and others in Metadata Management. Updated: May 2026.
900,644 professionals have used our research since 2012.