No more typing reviews! Try our Samantha, our new voice AI agent.

Palantir Foundry vs ibi Open Data Hub for Mainframe 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

ibi Open Data Hub for Mainf...
Ranking in Data Integration
61st
Average Rating
10.0
Reviews Sentiment
5.4
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Palantir Foundry
Ranking in Data Integration
5th
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
59
Ranking in other categories
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

As of June 2026, in the Data Integration category, the mindshare of ibi Open Data Hub for Mainframe is 0.7%, up from 0.2% compared to the previous year. The mindshare of Palantir Foundry is 2.0%, down from 3.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Palantir Foundry2.0%
ibi Open Data Hub for Mainframe0.7%
Other97.3%
Data Integration
 

Featured Reviews

it_user3876 - PeerSpot reviewer
Database Manager at a tech company with 51-200 employees
Provides High Reliability and Data Security
• Data in the datahub refreshes nightly. As the data only refreshes once every day, it is necessary to have to wait for any changes to thesource systems to become available.The daily refresh can be extremely useful for reconciling data. • DataHub only displays details of current members of the Organization. So it has much limited data available for generation of dynamic reports. • DataHub is volatile. The records are completely re-loaded each day. It puts burden on the system. • There are very few summary tables available due to storage of data in a detailed format. • The detailed information is not stored in the DataHub. It is stored in the relevant source system. Only commonly required data is stored within the DataHub.
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

"All staff members and users can request an account which can be accessed from all PCs on the company’s network."
"I like the data onboarding to Palantir Foundry and ETL creation."
"In terms of improvements, it helped us improve our data migration timelines by approximately 60 percent and improved the data accuracy and addressed the issues upfront by approximately 85 percent."
"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."
"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."
"The best features Palantir Foundry offers for my work include that building the ontology is very easy and it is easy to use."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"If I think of Foundry as being an implementation of Apache Spark and compare that to Databricks, it is easier for an organization to use Foundry."
"Combining data sources and hosting models in Palantir Foundry has helped my work because it is convenient to work in one environment rather than moving from one application to another, as Palantir Foundry allows for that one-stop shop where I can accomplish much of the work."
 

Cons

"DataHub is volatile; the records are completely re-loaded each day, which puts a burden on the system."
"However, Palantir Foundry's license fees comparative to others are quite high."
"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."
"If it was my choice, I wouldn't sign the contract with Palantir in the first place. I would probably stick to standard Databricks."
"They do not have a data center in Europe, and we have lots of personally identifiable information in our dataset that needs to be hosted by a third-party data center like Amazon or Microsoft Azure."
"Palantir Foundry can be improved by providing more third-party application support and more support for the Ontology software development kit to develop more native applications rather than just web applications."
"For example, exporting data from Palantir Foundry is very difficult and has many limitations."
"With Palantir Foundry, it is a part of the user tools that they provide. Their AI Assist that they use is something I have found that sometimes I get better results for when I do need help and aid."
"The solution's visualization and analysis could be improved."
 

Pricing and Cost Advice

Information not available
"Palantir Foundry is an expensive solution."
"The solution’s pricing is high."
"It's expensive."
"Palantir Foundry has different pricing models that can be negotiated."
report
Use our free recommendation engine to learn which Data Integration solutions are best for your needs.
902,417 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Construction Company
20%
Performing Arts
13%
Financial Services Firm
10%
Media Company
8%
Manufacturing Company
14%
Financial Services Firm
10%
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 Enterprise50
 

Questions from the Community

Ask a question
Earn 20 points
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...
 

Also Known As

iWay Data Hub, Data Hub, Information Builders Data Hub
No data available
 

Overview

 

Sample Customers

Ford Motor Company, City of Erlanger, Kentucky Police Dept., Helzberg Diamond Inc.
Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Find out what your peers are saying about Informatica, Microsoft, Palantir and others in Data Integration. Updated: June 2026.
902,417 professionals have used our research since 2012.