Microsoft Azure Data Box Reviews

We use the solution to migrate on-premise data and move legacy applications to the cloud.

We opted for Azure because Microsoft offers it with many legacy applications and data. They were moving to Azure because of in-house Microsoft expertise, and we specialize in Azure. It is a good fit with ease of integration there.

The support provided to partners is very generic, and finding a Microsoft specialist can be difficult to get on calls. The solution is straightforward with simple application migration, but plug-and-play AI is not involved simultaneously. There needs to be human intervention for the migration. It can be automated from end to end for SMBs, reducing cost and time for SMBs.

I have been using Microsoft Azure Data Box as an integrator for three years. We are using the latest version of the solution.

The product is stable, and I rate its stability an eight out of ten.

The solution is very scalable. We cater the solution to medium and enterprise.

The customer support is good.

Positive

The initial setup is straightforward and can be done by any Azure architect or anyone with little experience. However, the complexity of the migration project will affect the deployment. The number of applications, sites, and data involved affects it. One person can handle the setup for a simple migration of a couple of applications. However, more complex migrations may require multiple people.

It takes hours to complete the deployment.

There are two perspectives to deployment: some organizations completely outsource their Azure Data Box team to integrators, while others, such as large companies like Walmart and Microsoft, have their own dedicated in-house Azure team. It depends on the perspective.

The product’s pricing is normal for enterprises but higher for SMBs.

Enterprise customers prefer a longer contract, like 25 years, whereas SMBs prefer monthly billing.

I recommend the solution and rate it a nine out of ten.

There are a variety of use cases for Microsoft Azure Data Box. If you are a Microsoft shop, you do not want to work with glue, so that is why you would go with Microsoft Azure Data Box. If you are in a non-Microsoft environment, you don't want to work with a Microsoft product. But, it does provide a solution that integrates non-Microsoft products, both in AWS and Azure. At the end of the day, you do not want to pay for extra data storage. You do not want to pay both for AWS and Azure because you are going to need to replicate data across two cloud bases. It is all cost-based.

Microsoft tools are always better than those of other vendors. That is a fact. Microsoft Azure Data Box has much more usability than other tools like it. It is very intuitive. In AWS, everything is very techy, but they're very stable. At the end of the day, you have to pick your poison.

For me it doesn't work well, so I work in Microsoft and non-Microsoft shops. If you're a Microsoft shop, I would – undoubtedly, blindfolded – say go with Microsoft Azure Data Box. But, if you are a non-Microsoft shop, to use Microsoft Azure Data Box, you would need to integrate it with your other vendors, and whether or not that will be possible will depend on the platform or platforms that host them. If a specific vendor is hosted on AWS and you are on Azure, you have to pay for the data and there is no way around that.

I have been using Microsoft Azure Data Box for four years. 

The solution is scalable. I have not witnessed any problems with scalability. 

Sometimes I love the tech support and sometimes I hate them. This is the case with both AWS and Microsoft. From the perspective of an IT person, a lot can go wrong. There can be a problem with the solution you write, a piece of code not running well on their platform, or the platform not adapting to your solution. There is always that discussion and compromise.

Everything is a little bit difficult in the beginning. But, once you get used to it and how it works, it is just like any other solution. Once you get it going, there is no difference.

The return on investment you get from Microsoft Azure Data Box is subjective. Service providers and end users will have different ROIs. 

It all depends on the business and the use case in terms of how the organization is using the resources put towards the data. If you put enough resources into Microsoft Azure Data Box and evaluate your product on a continual basis, you can optimize it. If you take it at face value and start implementing it, you will not have a return on investment. However, if you go full support with all the services, then you can have a good investment. 

One note: If you use Microsoft Azure Data Box both on premise and the cloud, you will have twice the cost. You will have no return on investment there.

My advice is to deploy Microsoft Azure Data Box only if it makes sense to do so with the project. What are you looking for in the solution? Which product are you moving to the cloud? Who is the customer base? You have to take all of these factors into consideration before going one way or another.

We are a solution provider I have worked on two different projects with the Azure Data Box. It was used to back up all of the data from different teams for the purpose of DLP. We backed up more than 400 terabytes in total.

The Azure Data Box saves us a great deal of time when migrating data to Azure. Not only does it save time but you have to think of the cost savings, in terms of time, as well.

The most valuable feature is the ability to copy very large amounts of data and quickly have it uploaded to Azure. It is secure and there is no question about the loss of data.

It is very easy to plug in and to get the process started.

I am not confident in this device's ability to perform a network backup in our data center.

The stability is very good.

This solution is absolutely scalable because based on volume, we can scale it down.

This is a pay-as-you-go solution, where you pay for the amount of storage space that you are using.

Azure Data Box is something I would recommend for anyone who needs to migrate a large amount of data, for example from a data warehouse to the cloud.

I would rate this solution an eight out of ten.