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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
60th
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
13th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
32
Ranking in other categories
IT Operations Analytics (8th), Supply Chain Analytics (1st), Cloud Data Integration (10th), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of May 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 2.1%, down from 2.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Palantir Foundry2.1%
ibi Open Data Hub for Mainframe0.7%
Other97.2%
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."
"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 positively impacted my organization by enabling us to deliver projects quicker, as it organizes data from across the world into a dashboard that can be managed in one single location, accelerating business decisions made by the leadership team."
"The interface is really user-friendly."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"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 by saving time in creating agents and dashboards and definitely enhancing collaboration."
"It has been the platform for end to end data processing, manipulations, and reporting, greatly improved org's data reporting effort."
"Palantir Foundry is not just a data platform; it actually connects data engineering, analytics, operations, and decision-making all into one ecosystem."
 

Cons

"DataHub is volatile; the records are completely re-loaded each day, which puts a burden on the system."
"Some error messages can be very cryptic."
"There are some issues with scalability because when we are using a really large dataset, the system is rather slow."
"The one area where improvement could be made is the cost of the solution which is quite expensive."
"The problem is that interaction with outside applications can be difficult with the current setup that Palantir Foundry has."
"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."
"The workflow could be improved."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"As a developer, I find the limited documentation and less resource availability restrictive compared to other options such as AWS."
 

Pricing and Cost Advice

Information not available
"It's expensive."
"The solution’s pricing is high."
"Palantir Foundry is an expensive solution."
"Palantir Foundry has different pricing models that can be negotiated."
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Top Industries

By visitors reading reviews
Construction Company
17%
Performing Arts
13%
Media Company
8%
Financial Services Firm
8%
Manufacturing Company
13%
Financial Services Firm
10%
Government
8%
University
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise6
Large Enterprise27
 

Questions from the Community

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What needs improvement with Palantir Foundry?
Regarding points for improvement for Palantir Foundry, I see that they are improving day by day. In the last one to two years, I have seen many improvements compared to the two years that I have wo...
What is your primary use case for Palantir Foundry?
There are several use cases that we are working on with Palantir Foundry. The first thing is for data model creation for all our data engineering pipelines. That is one use case. Palantir Foundry a...
What advice do you have for others considering Palantir Foundry?
The visualization part in Palantir Foundry works for me at least if I want to see how the data is structured and for an initial analysis, but I would say it is not as matured as Power BI or Tableau...
 

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, Qlik and others in Data Integration. Updated: May 2026.
896,298 professionals have used our research since 2012.