The pricing for Microsoft Azure Machine Learning Studio is reasonable since it's pay as you go, meaning it won't cost excessively unless specific resources are used.
Solution Sales Specialist at Intent Solutions Group
Real User
Top 10
Dec 6, 2024
Pricing is considered to be top-segment and should be improved. I rate the pricing as three or four on a scale of one to ten in terms of affordability.
I would rate the pricing an eight out of ten, with ten being very expensive. Not very expensive, not very cheap. It was on a yearly basis, and there were also usage-based costs.
Learn what your peers think about Microsoft Azure Machine Learning Studio. Get advice and tips from experienced pros sharing their opinions. Updated: January 2026.
There is a lack of certainty with the solution's pricing. The risk is the pricing is high without you necessarily knowing. The workload drives the solution's pricing. If you give it a lot to do, it will cost a lot of money. It's about committing to how much you want to pay for. You don't necessarily know what you'll get for the price level that you agree. On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing a seven out of ten.
Principal Data Engineer at a tech services company with 11-50 employees
Real User
Top 5
Oct 2, 2023
ML Studio's pricing becomes a numbers game. When you're trying to run isolated experiments with simple datasets that are easily tracked, ML Studio does a very good job with its on-demand pricing. At the same time, provisioning the solution and some other internal tools might not be cost-optimized. It might just be directly provisioned from infrastructure direct cost. As your data scales and grows and your transformations become more complex, your cost will probably skyrocket because it will do nothing natively to help you save on that end. Other platforms help you run jobs and allow you to run them distributed with a simple configuration from the UI rather than having the optimized code to do so.
Technical Director at Integral Solutions (Asia) Pte Ltd
Real User
Aug 28, 2023
I rate the solution's pricing a four on a scale of one to ten, where one is cheap, and ten is expensive. There are some additional payments to be made apart from the licensing fees of the solution since buying Microsoft Azure Machine Learning Studio alone won't make it a complete solution. You will need the database and data lake services.
The product's pricing is reasonable. However, we do not have the option to limit data usage. In some accounts, we cannot control data usage and give customers enough budget for their consumption. They should work on adding a threshold for data usage so that customers can set their limits. It would be a great way to give customers more control over their Azure Machine Learning costs.
We have to pay for the solution's machine and storage. The cost depends on the specific models. Some of them cost 18 to 25 cents per hour. At the same time, some CPU machines cost €30 per hour.
Senior Data Analytics at a media company with 1,001-5,000 employees
Real User
Sep 9, 2022
My team didn't deal with the licensing for Microsoft Azure Machine Learning Studio, so I'm unable to comment on pricing, but the money that was spent on the tool was worth it.
Associate Director Of Technology at a tech vendor with 10,001+ employees
MSP
Jul 24, 2022
In terms of pricing, for any cloud solution, you should know the tricks of the trade and how to use it, otherwise, you'll end up paying a lot of money irrespective of the cloud provider, so at least for Microsoft Azure Machine Learning Studio pricing versus AWS, I would rate it three out of five, with one being the most expensive, and five being the cheapest. It could be cheaper, but you also have to be careful when choosing the plans, for example, consider the architecture and a lot of other factors before choosing your plan, if you don't want to end up paying more. If your cloud provider has an optimizer that seems to be available in every provider, that would keep alerting you in terms of resources not being used as much, then that would help you with budgeting.
We don't deal with licensing, that is something our customers are responsible for. My understanding is that the cost is $50 for the digitization of 1,000 pages. I think it should be reduced to somewhere between $20 to $30 per 1,000 pages so that we can make a better offer to our customers.
Head Of Analytics Platforms and Architecture at a manufacturing company with 10,001+ employees
Real User
Jan 27, 2021
The solution is quite expensive. It's something the organization should work on improving. We use this product on a pay-per-use basis, Therefore, there is no licensing fee. It's embedded in the cost of using the Studio.
Because client isa Microsoft shop, everything was Microsoft in terms of having solutions like Power BI and stuff like that. Azure is very useful and very inexpensive.
Director at a tech services company with 1,001-5,000 employees
Real User
Dec 9, 2019
From a developer's perspective, I find the price of this solution high. If somebody wants to learn how to use this platform then they have to spend money doing it. I know people who are interested in learning it but do not want to pay the full cost.
When we started using this solution, our licensing fees were approximately €1,000 (approximately $1,100 USD) monthly, but it was fluctuating. When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly. It was quite limited. We expected the rate to be higher than this, at perhaps €10,000 (approximately $11,000 USD) per month, but it wasn't the case.
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It has everything you need to create complete predictive analytics solutions in the cloud, from a large algorithm library, to a studio for building models, to an easy way to deploy your model as a web service. Quickly create, test, operationalize, and manage predictive models.Microsoft Azure Machine Learning Will Help You:
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The pricing for Microsoft Azure Machine Learning Studio is reasonable since it's pay as you go, meaning it won't cost excessively unless specific resources are used.
Pricing is considered to be top-segment and should be improved. I rate the pricing as three or four on a scale of one to ten in terms of affordability.
The product is not that expensive.
I would rate the costliness of the solution as a nine out of ten.
I would rate the pricing an eight out of ten, with ten being very expensive. Not very expensive, not very cheap. It was on a yearly basis, and there were also usage-based costs.
We have an enterprise contract.
There is a lack of certainty with the solution's pricing. The risk is the pricing is high without you necessarily knowing. The workload drives the solution's pricing. If you give it a lot to do, it will cost a lot of money. It's about committing to how much you want to pay for. You don't necessarily know what you'll get for the price level that you agree. On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing a seven out of ten.
ML Studio's pricing becomes a numbers game. When you're trying to run isolated experiments with simple datasets that are easily tracked, ML Studio does a very good job with its on-demand pricing. At the same time, provisioning the solution and some other internal tools might not be cost-optimized. It might just be directly provisioned from infrastructure direct cost. As your data scales and grows and your transformations become more complex, your cost will probably skyrocket because it will do nothing natively to help you save on that end. Other platforms help you run jobs and allow you to run them distributed with a simple configuration from the UI rather than having the optimized code to do so.
I rate the solution's pricing a four on a scale of one to ten, where one is cheap, and ten is expensive. There are some additional payments to be made apart from the licensing fees of the solution since buying Microsoft Azure Machine Learning Studio alone won't make it a complete solution. You will need the database and data lake services.
The product's pricing is reasonable. However, we do not have the option to limit data usage. In some accounts, we cannot control data usage and give customers enough budget for their consumption. They should work on adding a threshold for data usage so that customers can set their limits. It would be a great way to give customers more control over their Azure Machine Learning costs.
The platform's price is low. I rate its pricing a four out of ten.
We have to pay for the solution's machine and storage. The cost depends on the specific models. Some of them cost 18 to 25 cents per hour. At the same time, some CPU machines cost €30 per hour.
On a scale from one to ten, with ten being overpriced, I would rate the price of this solution at six.
I used the free student license for a few months to operate the solution, but I'll have to pay for it if I want to do more now.
The solution has a higher price. I'd rate it three out of ten in terms of affordability.
The solution cost is high.
My team didn't deal with the licensing for Microsoft Azure Machine Learning Studio, so I'm unable to comment on pricing, but the money that was spent on the tool was worth it.
In terms of pricing, for any cloud solution, you should know the tricks of the trade and how to use it, otherwise, you'll end up paying a lot of money irrespective of the cloud provider, so at least for Microsoft Azure Machine Learning Studio pricing versus AWS, I would rate it three out of five, with one being the most expensive, and five being the cheapest. It could be cheaper, but you also have to be careful when choosing the plans, for example, consider the architecture and a lot of other factors before choosing your plan, if you don't want to end up paying more. If your cloud provider has an optimizer that seems to be available in every provider, that would keep alerting you in terms of resources not being used as much, then that would help you with budgeting.
I'm not aware of how much the solution costs. I don't handle any of the licensing.
We don't deal with licensing, that is something our customers are responsible for. My understanding is that the cost is $50 for the digitization of 1,000 pages. I think it should be reduced to somewhere between $20 to $30 per 1,000 pages so that we can make a better offer to our customers.
There is a license required for this solution.
The licensing cost is very cheap. It's less than $50 a month would costs for multiple users.
The solution is quite expensive. It's something the organization should work on improving. We use this product on a pay-per-use basis, Therefore, there is no licensing fee. It's embedded in the cost of using the Studio.
Because client isa Microsoft shop, everything was Microsoft in terms of having solutions like Power BI and stuff like that. Azure is very useful and very inexpensive.
The pricing and licensing are difficult to explain to clients. Their rationale for what things cost and why are not easy to explain.
From a developer's perspective, I find the price of this solution high. If somebody wants to learn how to use this platform then they have to spend money doing it. I know people who are interested in learning it but do not want to pay the full cost.
When we started using this solution, our licensing fees were approximately €1,000 (approximately $1,100 USD) monthly, but it was fluctuating. When we got our first models and were ready for the user acceptance testing, our licensing fees were between €2,500 ($2,750 USD) and €3,000 ($3,300 USD) monthly. It was quite limited. We expected the rate to be higher than this, at perhaps €10,000 (approximately $11,000 USD) per month, but it wasn't the case.