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AWS Snowball vs Palantir Foundry comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Jul 11, 2024

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

AWS Snowball
Ranking in Data Migration Appliances
1st
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
10
Ranking in other categories
Cloud Migration (15th)
Palantir Foundry
Ranking in Data Migration Appliances
2nd
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
62
Ranking in other categories
Data Integration (2nd), IT Operations Analytics (4th), Supply Chain Analytics (1st), Cloud Data Integration (4th), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of September 2026, in the Data Migration Appliances category, the mindshare of AWS Snowball is 34.8%, down from 37.7% compared to the previous year. The mindshare of Palantir Foundry is 6.0%, up from 3.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Migration Appliances Mindshare Distribution
ProductMindshare (%)
AWS Snowball34.8%
Palantir Foundry6.0%
Other59.2%
Data Migration Appliances
 

Featured Reviews

Kevin-Davis - PeerSpot reviewer
Global CTO AWS Business Group at Eviden
Seamless data transfer and efficient migration with customizable storage sizes
I like that I can take data and send it straight to S3 when it loads in. The interface for getting my data onto the Snowball is so streamlined. I don't know if you've ever seen it before. It's really cool. I connect them to the backplane of our existing network. I'm able to address it quickly and move the data quickly inside my customers' data centers. There's a little screen on it, which changes the UPS codes and all that stuff. The label and everything AWS electronic, so I don't have to deal with shipping issues. It makes it super simple and easy to use from end to end.
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

"I like that I can take data and send it straight to S3 when it loads in."
"The support team's awesome, and they've always been very responsive."
"The interface is great! It's user-friendly."
"The flexibility of AWS Snowball is valuable. Its security allows for the ability to move and secure data without concern if the device is lost and the option to trace it back to AWS data centers."
"AWS offers managed services which save time and reduce administrative overhead."
"If you have a large amount of data, it's a perfect way to move it to the cloud."
"The most valuable features of AWS Snowball for me are its security measures and its flexibility."
"It's a nice way of shipping a lot of data without using a network."
"Palantir Foundry has positively impacted my organization by saving time in creating agents and dashboards and definitely enhancing collaboration."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"The strength of Palantir Foundry is that there are no limitations, it is well organized, and the data is very secure."
"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."
"With Palantir Foundry, it helps us have better benefits and better return on investment, and also accelerates the right decision in the market."
"I like the data onboarding to Palantir Foundry and ETL creation."
"The virtualization tool is useful."
 

Cons

"It's not cheap."
"I think AWS Snowball could improve by expanding its availability to more countries."
"It does have room for improvement. The ability to better ingest some of the big data."
"24/7 support is more expensive on AWS compared to Azure."
"The costs of services the customer needs also matter, such as storage requirements and whether storage is rational."
"There's always room for improvement as you use the service more and gain expertise. Some challenges I've faced include the time factor (data transfer can be time-consuming), data validation after the transfer, risks associated with physical handling and shipping of the device, and ensuring data security during transit."
"It would be helpful if Snowball provided more kinds of connectivity. That will make it easier to add and move data."
"The stability of the solution isn't ideal and should be improved."
"The workflow could be improved. Although it works rather seamlessly, the workflow is too complicated sometimes."
"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."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"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 frontend capabilities of Palantir Foundry could be improved."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"The Workshop application could be improved because it is not very customizable, but it is still very strong."
"There is a learning curve to Palantir Foundry, and better documentation would really help because while documentation exists, not everything is covered."
 

Pricing and Cost Advice

"It's not a cheap solution, but the price is right for the product."
"The tool's pricing depends on the type of Snowball device you choose, the amount of data you need to transfer, and the service fees involved. There’s a standard price for larger data transfers and a flat job fee, which includes the first ten days of on-site usage. Typically, there are no additional data transfer fees."
"The solution’s pricing is high."
"Palantir Foundry has different pricing models that can be negotiated."
"It's expensive."
"Palantir Foundry is an expensive solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
8%
Comms Service Provider
8%
Manufacturing Company
14%
Financial Services Firm
10%
Government
7%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise1
Large Enterprise6
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise7
Large Enterprise51
 

Questions from the Community

Which is better - Microsoft Azure Data Box or AWS Snowball?
Microsoft Azure Databox is a 45-pound, super rugged, tamper-resistant, human-managed hardware appliance that can transfer up to 100TB of data capacity to copy, store, then send to the Azure cloud. ...
What is your experience regarding pricing and costs for AWS Snowball?
Depending of what is your priority; UseAWS Snowball if you are heavily invested in AWS or need edge computing features Choose Azure Data Box for smooth integration with Azure and potentially lower ...
What needs improvement with AWS Snowball?
It's difficult to make a comparison and it depends on the customer. When analyzing costs, I must see how the customer uses AWS, Azure, or Google. Google is particularly interesting, for example, fo...
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...
 

Also Known As

Amazon AWS Snowball, Amazon Snowball, Snowball
No data available
 

Overview

 

Sample Customers

Wazee Digital, Craftsy, Live Nation, Essess
Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Find out what your peers are saying about AWS Snowball vs. Palantir Foundry and other solutions. Updated: September 2026.
913,924 professionals have used our research since 2012.