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AWS Snowball vs Palantir Foundry comparison

 

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 (13th)
Palantir Foundry
Ranking in Data Migration Appliances
3rd
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
31
Ranking in other categories
Data Integration (13th), IT Operations Analytics (8th), Supply Chain Analytics (1st), Cloud Data Integration (10th), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of May 2026, in the Data Migration Appliances category, the mindshare of AWS Snowball is 32.8%, down from 40.4% compared to the previous year. The mindshare of Palantir Foundry is 7.0%, up from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Migration Appliances Mindshare Distribution
ProductMindshare (%)
AWS Snowball32.8%
Palantir Foundry7.0%
Other60.2%
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

"If you have a large amount of data, it's a perfect way to move it to the cloud."
"The solution is elastic."
"The support team's awesome, and they've always been very responsive."
"I like that I can take data and send it straight to S3 when it loads in."
"The way the data is moved is very clever. Also, the interface is very simple and 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."
"The solution is elastic."
"We are a very large company with around 20 million users that include architects, developers, and admin staff, and it's a very nice service we would highly recommend."
"The AI engine that comes with Palantir Foundry is quite interesting."
"The virtualization tool is useful."
"The ease of use is my favorite feature. We're able to build different models and projects or combine different projects to build one use case."
"The interface is really user-friendly."
"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."
"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."
"We believe that the client has improved their efficiency compared to their previous working model; they have more clarity and, above all, more control over the data."
"It's scalable."
 

Cons

"AWS support could be more responsive."
"It would be helpful if Snowball provided more kinds of connectivity. That will make it easier to add and move data."
"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."
"24/7 support is more expensive on AWS compared to Azure."
"It's not cheap."
"The stability of the solution isn't ideal and should be improved."
"The costs of services the customer needs also matter, such as storage requirements and whether storage is rational."
"It's not an easy product to start using for a beginner, but if you're a professional, it's easy to understand."
"Cost of this solution is quite high."
"The workflow could be improved. Although it works rather seamlessly, the workflow is too complicated sometimes."
"There are still a lot of changes required in Palantir Foundry to make it more usable or easy to use."
"Some error messages can be very cryptic."
"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."
"When I started with Palantir Foundry, the initial deployment was not that great. I was not able to figure out certain things, because there are certain coding patterns that need to be followed in order to make it run."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"The solution's visualization and analysis could be improved."
 

Pricing and Cost Advice

"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."
"It's not a cheap solution, but the price is right for the product."
"Palantir Foundry is an expensive solution."
"It's expensive."
"Palantir Foundry has different pricing models that can be negotiated."
"The solution’s pricing is high."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
10%
Manufacturing Company
7%
Retailer
7%
Manufacturing Company
13%
Financial Services Firm
10%
Government
8%
University
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 Business5
Midsize Enterprise6
Large Enterprise26
 

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?
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

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: April 2026.
896,298 professionals have used our research since 2012.