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AWS Snowball vs IBM Turbonomic comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 1, 2025

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 Cloud Migration
12th
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
10
Ranking in other categories
Data Migration Appliances (1st)
IBM Turbonomic
Ranking in Cloud Migration
5th
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
205
Ranking in other categories
Cloud Management (4th), Virtualization Management Tools (4th), IT Financial Management (1st), IT Operations Analytics (4th), Cloud Analytics (1st), Cloud Cost Management (1st), AIOps (5th)
 

Mindshare comparison

As of May 2025, in the Cloud Migration category, the mindshare of AWS Snowball is 0.7%, up from 0.1% compared to the previous year. The mindshare of IBM Turbonomic is 4.0%, down from 5.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Migration
 

Featured Reviews

Kevin-Davis - PeerSpot reviewer
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.
Keldric Emery - PeerSpot reviewer
Saves time and costs while reducing performance degradation
It's been a very good solution. The reporting has been very, very valuable as, with a very large environment, it's very hard to get your hands on the environment. Turbonomic does that work for you and really shows you where some of the cost savings can be done. It also helps you with the reporting side. Me being able to see that this machine hasn't been used for a very long time, or seeing that a machine is overused and that it might need more RAM or CPU, et cetera, helps me understand my infrastructure. The cost savings are drastic in the cloud feature in Azure and in AWS. In some of those other areas, I'm able to see what we're using, what we're not using, and how we can change to better fit what we have. It gives us the ability for applications and teams to see the hardware and how it's being used versus how they've been told it's being used. The reporting really helps with that. It shows which application is really using how many resources or the least amount of resources. Some of the gaps between an infrastructure person like myself and an application are filled. It allows us to come to terms by seeing the raw data. This aspect is very important. In the past, it was me saying "I don't think that this application is using that many resources" or "I think this needs more resources." I now have concrete evidence as well as reporting and some different analytics that I can show. It gives me the evidence that I would need to show my application owners proof of what I'm talking about. In terms of the downtime, meantime, and resolution that Turbonomic has been able to show in reports, it has given me an idea of things before things happen. That is important as I would really like to see a machine that needs resources, and get resources to it before we have a problem where we have contention and aspects of that nature. It's been helpful in that regard. Turbonomic has helped us understand where performance risks exist. Turbonomic looks at my environment and at the servers and even at the different hosts and how they're handling traffic and the number of machines that are on them. I can analyze it and it can show me which server or which host needs resources, CPU, or RAM. Even in Azure, in the cloud, I'm able to see which resources are not being used to full capacity and understand where I could scale down some in order to save cost. It is very, very helpful in assessing performance risk by navigating underlying causes and actions. The reason why it's helpful is because if there's a machine that's overrunning the CPU, I can run reports every week to get an idea of machines that would need CPU, RAM, or additional resources. Those resources could be added by Turbonomic - not so much by me - on a scheduled basis. I personally don't have to do it. It actually gives me a little bit of my life back. It helps me to get resources added without me physically having to touch each and every resource myself. Turbonomic has helped to reduce performance degradation in the same way as it's able to see the resources and see what it needs and add them before a problem occurs. It follows the trends. It sees the trends of what's happening and it's able to add or take away those resources. For example, we discuss when we need to do certain disaster recovery tests. Over the years, Turbo will be able to see, for example, around this time of year that certain people ramp up certain resources in an environment, and then it will add the resources as required. Another time of year, it will realize these resources are not being used as much, and it takes those resources away. In this way, it saves money and time while letting us know where we are. We've saved a great deal of time using this product when I consider how I'd have to multiply myself and people like me who would have to add resources to devices or take resources away. We've saved hundreds of hours. Most of the time those hours would have to be after hours as well, which are more valuable to me as that's my personal time. Those saved hours are across months, not years. I would consider the number of resources that Turbonomic is adding and taking away and the placement (if I had to do it all myself) would end up being hundreds of hours monthly that would be added without the help of Turbonomic. It helps us to meet SLAs mainly due to the fact that we're able to keep the servers going and to keep the servers in an environment, to keep them to where (if we need to add resources) we can add them at any given time. It will keep our SLAs where they need to be. If we were to have downtime due to the fact that we had to add resources or take resources away and it was an emergency, then that would prevent us from meeting our SLAs. We also use it to monitor Azure and to monitor our machines in terms of the resources that are out there and the cost involved. In a lot of cases, it does a better job of giving us cost information than Azure itself does. We're able to see the cost per machine. We're able to see the unattached volume and storage that we are paying for. It gives us a great level of insight. Turbonomic gives us the time to be able to focus on innovation and ongoing modernization. Some of the tasks that it does are tasks that I would not necessarily have to do. It's very helpful in that I know that the resources are there where they need to be and it gives me an idea of what changes need to be made or what suggestions it's making. Even if I don't take them, I'm able to get a good idea of some best practices through Turbonomic. One of the ways that Turbonomic does to help bring new resources to market is that we are now able to see the resources (or at least monitor the resources) before they get out to the general public within our environment. We saw immediate value from the product in the test environment. We set it up in a small test environment and we started with just placement and we could tell that the placement was being handled more efficiently than what VMware was doing. There was value for us in placement alone. Then, after we left the placement, we began to look at the resources and there were resources. We immediately began to see a change in the environment. It has made the application and performance better, mainly due to the fact that we are able to give resources and take resources away based on what the need is. Our expenses, definitely, have been in a better place based on the savings that we've been able to make in the cloud and on-prem. Turbonomic has been very helpful in that regard. We've been able to see the savings easily based on the reports in Turbonomic. That, and just seeing the machines that are not being used to capacity allows us to set everything up so it runs a bit more efficiently.

Quotes from Members

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

Pros

"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."
"The solution is elastic."
"The solution is elastic."
"The features I like best are the tool's high capacity, scalability, end-to-end encryption for data security, ease of use, durability, and cost-effectiveness. It's particularly cost-effective for transferring large amounts of data compared to high-speed internet transfers."
"The support team's awesome, and they've always been very responsive."
"AWS helps save time and costs, being a managed cloud provider with evolving services."
"The way the data is moved is very clever. Also, the interface is very simple and user-friendly."
"It is a good holistic platform that is easy to use. It works pretty well."
"It has automated a lot of things. We have saved 30 to 35 percent in human resource time and cost, which is pretty substantial. We don't have a big workforce here, so we have to use all the automation we can get."
"The automated memory balancing, where it looks at whether it's being used in the most efficient way and adds or takes away memory, is the best part. If it didn't do that, it would be something that I would have to do. We have too many machines for one person to do that. The automation helps me in that it is done in a really efficient way and a balanced way because of the policies. It really helps."
"We've saved hundreds of hours. Most of the time those hours would have to be after hours as well, which are more valuable to me as that's my personal time."
"We can manage multiple environments using a single pane of glass, which is something that I really like."
"Turbonomic helps us right-size virtual machines to utilize the available infrastructure components available and suggest where resources should exist. We also use the predictive tool to forecast what will happen when we add additional compute-demanding virtual machines or something to the environment. It shows us how that would impact existing resources. All of that frees up time that would otherwise be spent on manual calculation."
"The tool provides the ability to look at the consumption utilization over a period of time and determine if we need to change that resource allocation based on the actual workload consumption, as opposed to how IT has configured it. Therefore, we have come to realize that a lot of our workloads are overprovisioned, and we are spending more money in the public cloud than we need to."
"We like that Turbonomic shows application metrics and estimates the impact of taking a suggested action. It provides us a map of resource utilization as part of its recommendation. We evaluate and compare that to what we think would be appropriate from a human perspective to that what Turbonomic is doing, then take the best action going forward."
 

Cons

"If AWS Snowball is intercepted, there is a potential risk of unauthorized access to the data."
"I think AWS Snowball could improve by expanding its availability to more countries."
"24/7 support is more expensive on AWS compared to Azure."
"AWS support could be more responsive."
"Snowball is not interesting and is a pain to deal with."
"It's not an easy product to start using for a beginner, but If you're a professional, it's easy to understand."
"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."
"Recovering resources when they're not needed is not as optimized as it could be."
"I would like Turbonomic to add more services, especially in the cloud area. I have already told them this. They can add Azure NetApp Files. They can add Azure Blob storage. They have already added Azure App service, but they can do more."
"The GUI and policy creation have room for improvement. There should be a better view of some of the numbers that are provided and easier to access. And policy creation should have it easier to identify groups."
"After running this solution in production for a year, we may want a more granular approach to how we utilize the product because we are planning to use some of its metrics to feed into our financial system."
"The reporting needs to be improved. It's important for us to know and be able to look back on what happened and why certain decisions were made, and we want to use a custom report for this."
"Turbonomic can modernize the look and feel, making it more user-friendly to access and obtain information."
"The one point is the reporting. We do have reports out of it, but they're not the level of graphical detail I would like."
"Since the introduction of a HTML 5 based interface, our main - but minor - criticism of a less than intuitive operation managers' GUI would be the area of improvement."
 

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."
"If you're a super-small business, it may be a little bit pricey for you... But in large, enterprise companies where money is, maybe, less of an issue, Turbonomic is not that expensive. I can't imagine why any big company would not buy it, for what it does."
"It was an annual buy-in. You basically purchase it based on your host type stuff. The buy-in was about 20K, and the annual maintenance is about $3,000 a year."
"We see ROI in extended support agreements (ESA) for old software. Migration activities seem to be where Turbonomic has really benefited us the most. It's one click and done. We have new machines ready to go with Turbonomic, which are properly sized instead of somebody sitting there with a spreadsheet and guessing. So, my return on investment would certainly be on currency, from a software and hardware perspective."
"I have not seen Turbonomic's new pricing since IBM purchased it. When we were looking at it in my previous company before IBM's purchase, it was compatible with other tools."
"It is an endpoint type license, which is fine. It is not overly expensive."
"I don't know the current prices, but I like how the licensing is based on the number of instances instead of sockets, clusters, or cores. We have some VMs that are so heavy I can only fit four on one server. It's not cost-effective if we have to pay more for those. When I move around a VM SQL box with 30 cores and a half-terabyte of RAM, I'm not paying for an entire socket and cores where people assume you have at least 10 or 20 VMs on that socket for that pricing."
"I know there have been some issues with the billing, when the numbers were first proposed, as to how much we would save. There was a huge miscommunication on our part. Turbonomic was led to believe that we could optimize our AWS footprint, because we didn't know we couldn't. So, we were promised savings of $750,000. Then, when we came to implement Turbonomic, the developers in AWS said, "Absolutely not. You're not putting that in our environment. We can't scale down anything because they coded it." Our AWS environment is a legacy environment. It has all these old applications, where all the developers who have made it are no longer with the company. Those applications generate a ton of money for us. So, if one breaks, we are really in trouble and they didn't want to have to deal with an environment that was changing and couldn't be supported. That number went from $750,000 to about $450,000. However, that wasn't Turbonomic's fault."
"Everybody tells me the pricing is high. But the ROIs are great."
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Top Industries

By visitors reading reviews
Computer Software Company
15%
Financial Services Firm
14%
Government
9%
Manufacturing Company
8%
Financial Services Firm
14%
Computer Software Company
13%
Manufacturing Company
9%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

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 do you like most about AWS Snowball?
The most valuable features of AWS Snowball for me are its security measures and its flexibility.
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 is your experience regarding pricing and costs for Turbonomic?
It offers different scenarios. It provides more capabilities than many other tools available. Typically, its price is set as a percentage of the consumption of some of our customers' services. The ...
What needs improvement with Turbonomic?
The implementation could be enhanced.
What is your primary use case for Turbonomic?
We use IBM Turbonomic to automate our cloud operations, including monitoring, consolidating dashboards, and reporting. This helps us get a consolidated view of all customer spending into a single d...
 

Also Known As

Amazon AWS Snowball, Amazon Snowball, Snowball
Turbonomic, VMTurbo Operations Manager
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

Wazee Digital, Craftsy, Live Nation, Essess
IBM, J.B. Hunt, BBC, The Capita Group, SulAmérica, Rabobank, PROS, ThinkON, O.C. Tanner Co.
Find out what your peers are saying about AWS Snowball vs. IBM Turbonomic and other solutions. Updated: April 2025.
851,491 professionals have used our research since 2012.