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Julia Frohwein - PeerSpot reviewer
Senior Director of Delivery at PeerSpot (formerly IT Central Station)
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What is your primary use case for AWS Snowball?

How do you or your organization use this solution?

Please share with us so that your peers can learn from your experiences.

Thank you!

PeerSpot user
4 Answers
AnupChapalgaonkar - PeerSpot reviewer
Cloud Solution Architect at Tech Mahindra
Real User
Top 20Leaderboard
16 January 20

We are trying to model the solution with some other vendors like Azure on a public cloud environment. We are creating some scale models will identify the public cloud networks over the internet. We are trying to evaluate the functionality.

BaijuShah - PeerSpot reviewer
CEO at Ebiashara Africa Limited
Real User
Top 10Leaderboard
12 December 19

Our primary use case for Snowball is ETL data extract. Transform and load. That's what we're using Snowball for at the moment. So basically adding an analytical layer on top of the current data warehouses for some of our customers.

Lead Developer at a manufacturing company with 10,001+ employees
26 November 19

This is a product used to upload huge amounts of data into the cloud. That's the scope of it. For that purpose, it's authentic, and I don't think that there are competitive alternatives available. You can upload huge amounts of data like archiving.

Aymen Jlassi - PeerSpot reviewer
Technical Consultant / CTO at a tech services company with 1-10 employees
24 September 19

I primarily have used the solution to move data. If we have a huge amount of data and we need to move it, we request a Snowball, a box from Amazon. It's shipped to the customer location and we connect it to the environment.

Related Questions
Netanya Carmi - PeerSpot reviewer
Content Manager at PeerSpot (formerly IT Central Station)
Nov 24, 2021
See 1 answer
24 November 21
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. This solution is easy to use, plugs directly into your network, and uses NAS protocols. The device uses 256-bit encryption on the data to ensure safe transport. Microsoft Azure Databox is a huge time saver when migrating data to Azure. Microsoft Databox is pricey and takes a good level of expertise to run and manage. Some of our team were not confident that Microsoft Databox could perform a complete network backup of our data AWS Snowball is a secure, rugged data transport device (weighing in at 47 pounds) with on-board storage and compute capabilities. This solution can accelerate data transfers into and out of Amazon Web Services. AWS Snowball helps us save time and cut costs. What we like most about it is the prepaid shipping label in the E Ink display that will automatically update to indicate the correct AWS partner location to ship to, and you can track the job status using several different options from text messaging or directly from the console. AWS Snowball is not an easy solution to jump into; there is a bit of a learning curve. Using AWS Snowball we had some instances where things were a little buggy. There are also some potential stability issues that should be investigated. Conclusion: AWS was first to the databox market with Snowball; then Microsoft answered with Azure Databox. AWS Snowball remains a few steps ahead with certain features. The smart E Ink labeling coupled with Amazon’s incredible reach with global shipping really sets them apart and keeps them way ahead in the actual movement of the databoxes back and forth from one physical location to the other. Additionally, AWS Snowball seems to be more adept at the actual migration of data to the cloud, the speed of transfer, and the amount of data AWS Snowball is capable of moving - e.g. Petabytes as opposed to Terabytes with Microsoft Azure Databox. AWS Snowball just seems to do it better. However, AWS Snowball is most effective in an AWS ecosystem, and of course, Azure Databox works primarily with Azure Cloud. Which works better for you may depend on the ecosystem in which you are currently working.