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Palantir Foundry vs Skyvia comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Mar 1, 2026

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
2nd
Ranking in Cloud Data Integration
4th
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
62
Ranking in other categories
IT Operations Analytics (4th), Supply Chain Analytics (1st), Data Migration Appliances (2nd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
Skyvia
Ranking in Data Integration
62nd
Ranking in Cloud Data Integration
29th
Average Rating
9.0
Reviews Sentiment
7.8
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of September 2026, in the Cloud Data Integration category, the mindshare of Palantir Foundry is 3.9%, down from 5.7% compared to the previous year. The mindshare of Skyvia is 1.5%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
Palantir Foundry3.9%
Skyvia1.5%
Other94.6%
Cloud 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.
RH
CTO & Developer at a consultancy with self employed
The product works, is simple to use, and is reliable.
Error handling. This has caused me many problems in the past. When an error occurs, the event on the connection that is called does not seem to behave as documented. If I attempt a retry or opt not to display an error dialog, it does it anyway. In all fairness, I have never reported this. I think it is more important that a unique error code is passed to the error event that identifies a uniform type of error that occurred, such as ecDisconnect, eoInvalidField. It is very hard to find what any of the error codes currently passed actually mean. A list would be great for each database engine. Trying to catch an exception without displaying the UniDAC error message is impossible, no matter how you modify the parameters in the OnError of the TUniConnection object. I have already implemented the following things myself. They are suggestions rather than specific requests. Copy Datasets: This contains an abundance of redundant options. I think that a facility to copy one dataset to another in a single call would be handy. Redundancy: I am currently working on this. I have extended the TUniConnection to have an additional property called FallbackConnection. If the TUniConnection goes offline, the connection attempts to connect the FallbackConnection. If successful, it then sets the Connection properties of all live UniDatasets in the app to the FallbackConnection and re-opens them if necessary. The extended TUniConnection holds a list of datasets that were created. Each dataset is responsible for registering itself with the connection. This is a highly specific feature. It supports an offline mode that is found in mission critical/point of sale solutions. I have never seen it implement before in any DACs, but I think it is a really unique feature with a big impact. Dataset to JSON/XML: A ToSql function on a dataset that creates a full SQL Text statement with all parameters converted to text (excluding blobs) and included in the returned string. Extended TUniScript:- TMyUniScript allows me to add lines of text to a script using the normal dataset functions, Script.Append, Script.FieldByName(‘xxx’).AsString := ‘yyy’, Script.AddToScript and finally Script.Post, then Script.Commit. The AddToScript builds the SQL text statement and appends it to the script using #e above. Record Size Calculation. It would be great if UniDac could estimate the size of a particular record from a query or table. This could be used to automatically set the packet fetch/request count based on the size of the Ethernet packets on the local area network. This I believe would increase performance and reduce network traffic for returning larger datasets. I am aware that this would also be a unique feature to UniDac but would gain a massive performance enhancement. I would suggest setting the packet size on the TUniConnection which would effect all linked datasets.

Quotes from Members

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

Pros

"The solution offers very good end-to-end capabilities."
"The best features Palantir Foundry offers for my work include that building the ontology is very easy and it is easy to use."
"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."
"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."
"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."
"It has been the platform for end to end data processing, manipulations, and reporting, greatly improved org's data reporting effort."
"Palantir Foundry has positively impacted an organization where I previously worked, as it was a platform where developers, DevOps, and users could make changes together."
"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."
"For what it offers, I think this solution is a must for any Delphi programmer."
 

Cons

"From an organizational perspective, it is advisable to note that initially, the cost may be low, but as time passes, cost can be a significant factor in deciding whether to continue using Palantir Foundry or not, so those considerations should be taken into account."
"The solution could use more online documentation for new users."
"However, I observe a potential drawback concerning market trends; as software becomes more accessible with individuals developing applications independently, there is a risk posed to Palantir Foundry, which combines multiple core functionalities."
"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."
"The one area where improvement could be made is the cost of the solution which is quite expensive."
"However, Palantir Foundry's license fees comparative to others are quite high."
"The data lineage was challenging. It's hard to track data from the sources as it moves through stages. Informatica EDC can easily capture and report it because it talks to the metadata. This is generated across those various staging points."
"Palantir Foundry could be improved by addressing the need for some coding in the Workshop since we cannot expect 100% no-code functionality, especially when dealing with dynamic user input, which requires writing functions in the Code Repository."
"Error handling has caused me many problems in the past; when an error occurs, the event on the connection that is called does not seem to behave as documented."
 

Pricing and Cost Advice

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

By visitors reading reviews
Manufacturing Company
14%
Financial Services Firm
10%
Government
7%
Comms Service Provider
6%
Construction Company
15%
Performing Arts
15%
Outsourcing Company
10%
Comms Service Provider
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise7
Large Enterprise51
No data available
 

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...
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Also Known As

No data available
Skyvia, Skyvia Data Integration
 

Overview

 

Sample Customers

Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Boeing, Sony, Honda, Oracle, BMW, Samsung
Find out what your peers are saying about Amazon Web Services (AWS), Informatica, Palantir and others in Cloud Data Integration. Updated: September 2026.
913,806 professionals have used our research since 2012.