A platform for developing generative AI solutions and custom copilots. Azure AI Studio includes catalog of models from OpenAI, Hugging Face, and Meta, that can be applied over in-house data. It is intended for professional software developers—including cloud architects and technical decision-makers—who want to create generative AI applications and custom copilot experiences.
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Microsoft R Open / Revolution R Enterprise
Score8.9 out of 10
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Microsoft R Open and Revolution R Enterprise are big data R distribution for servers, Hadoop clusters, and data warehouses. Microsoft acquired original developer Revolution Analytics in 2016.
Microsoft R is available in two editions: Microsoft R Open (formerly Revolution R Open) and Revolution R Enterprise.
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Pricing
Azure AI Studio
Microsoft R Open / Revolution R Enterprise
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure AI Studio
Microsoft R Open / Revolution R Enterprise
Free Trial
No
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Features
Azure AI Studio
Microsoft R Open / Revolution R Enterprise
Platform Connectivity
Comparison of Platform Connectivity features of Azure AI Studio and Microsoft R Open / Revolution R Enterprise
Feature
Azure AI Studio
-
Ratings
Microsoft R Open / Revolution R Enterprise
5.3
3 Ratings
45% below category average
Connect to Multiple Data Sources
00 Ratings
6.13 Ratings
Extend Existing Data Sources
00 Ratings
6.03 Ratings
Automatic Data Format Detection
00 Ratings
6.03 Ratings
MDM Integration
00 Ratings
3.01 Ratings
Data Exploration
Comparison of Data Exploration features of Azure AI Studio and Microsoft R Open / Revolution R Enterprise
Feature
Azure AI Studio
-
Ratings
Microsoft R Open / Revolution R Enterprise
7.0
3 Ratings
18% below category average
Visualization
00 Ratings
7.03 Ratings
Interactive Data Analysis
00 Ratings
7.03 Ratings
Data Preparation
Comparison of Data Preparation features of Azure AI Studio and Microsoft R Open / Revolution R Enterprise
Feature
Azure AI Studio
-
Ratings
Microsoft R Open / Revolution R Enterprise
4.8
3 Ratings
52% below category average
Interactive Data Cleaning and Enrichment
00 Ratings
5.13 Ratings
Data Transformations
00 Ratings
5.03 Ratings
Data Encryption
00 Ratings
3.01 Ratings
Built-in Processors
00 Ratings
6.03 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Azure AI Studio and Microsoft R Open / Revolution R Enterprise
Feature
Azure AI Studio
-
Ratings
Microsoft R Open / Revolution R Enterprise
6.0
3 Ratings
34% below category average
Multiple Model Development Languages and Tools
00 Ratings
5.03 Ratings
Automated Machine Learning
00 Ratings
5.02 Ratings
Single platform for multiple model development
00 Ratings
8.03 Ratings
Self-Service Model Delivery
00 Ratings
6.03 Ratings
Model Deployment
Comparison of Model Deployment features of Azure AI Studio and Microsoft R Open / Revolution R Enterprise
I am deploying a lot of pipelines and making a lot of variants of these pipeline segments, like different types of vector search techniques. The simple way to mix and fix these segments to run the whole pipelines in notebooks options are big overhead killer. The playground which provides a test sandbox helps a lot to evaluate LMs if they are the best fit for our use-case even before deploying and startup with the costing angle.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
If you are a MS shop specifically, or have more generic data requirement needs from Microsoft sourced data this will work well. If you have a lot of disparate data across a number of unique platforms/cloud systems/3rd party hosted data warehouses then this product will have issues or a lack of documentation on the net. Performance-wise this product is equal to other R platforms out there.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Wide Catalog of Models is a beautiful feature for all who want to evaluate a lot of models before proceeding with any client use case for the best performance.
Playground for testing and evaluating visual comparisons on so many metrics like latency, cost, and output time.
Integration with other Cloud services, this makes the full complete solutioning and vision complete, from storage to compute.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Model Catalog can have a feature to show basic compute and the cost of running the model on that compute. With latency metrics, I generally need to do a lot of research before losing some dollars on deployment on hit and trials.
Documentation generator for pipelines deployed in notebooks, generally developers use notebooks for experimentation, where logging them can be a big overhead.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
In general, Revolution Analytics brings a lot of value to the organization. The renewal decision would be based on return on investment in terms of quantified actionable insights that are getting generated against the cost of the product. Additionally, market brand of the tool and reputation risk in terms of possible acquisition and its impact to overall organizational analytic strategy would be considered as well.
Microsoft Foundry includes the existing AI Services. It's quite literally Cognitive Services under the hood, so in that sense, if you're building a new "AI app" today where you would have deployed an AI Services Account, you can deploy Microsoft Foundry instead. The side benefit of that is that Foundry also includes model deployments, and more than just the OpenAI models. So, it removes the need for deploying a separate Azure OpenAI Service in some circumstances. Then finally it has agent capabilities too. So, if you're developing and deploying agents as part of your solution (which usually interface with a model) then you can do that from there as well. Effectively it's meant to be a one-stop-shop for all things AI, just like Fabric is for data.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
It is good, easy to use, improvements are being made to the product and more info being shared in the community. It just needs some more time to become more integrated to other platforms and tools/data out there.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Generally support comes through the forums and user generated channels which are helpful, easy to access, quickly turned around and provided by knowledgeable users. However the support channels are not employees and the channels are often used as a way to learn quick difficult elements of R. Better design, users interface and tutorial options would alleviate the need for this sort of interaction.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Azure AI Studio were the pioneers of DevOPs, so MLOPs feels quite a bit better on this platform than Google. Azure brought OpenAI into the system which made the Organization to shift from any other platform to Azure AI Studio.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The two are different products for different purposes. But for someone who has little or no experience in R programming, Power BI would be better for starting with. Having said that, Microsoft R is built on R, thus allowing for customization of complex calculations not typically available otherwise.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Onboarding a team member for the codebase is slightly slower, almost 20% slower. As codebase sharing is like a git pull from repos, whereas here we need to provide all the access.
I have experienced scaling up speed almost 50% faster as per compared with on-prem solutions. ML models are faster deployed in terms of on-prem deployments.
10 times better Azure AI Studio for cost visibility over any other solution.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info