Microsoft Azure is a cloud computing platform and infrastructure for building, deploying, and managing applications and services through a global network of Microsoft-managed datacenters.
$29
per month
Microsoft R Open / Revolution R Enterprise
Score 8.9 out of 10
N/A
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.
N/A
Pricing
Microsoft Azure
Microsoft R Open / Revolution R Enterprise
Editions & Modules
Developer
$29
per month
Standard
$100
per month
Professional Direct
$1000
per month
Basic
Free
per month
No answers on this topic
Offerings
Pricing Offerings
Microsoft Azure
Microsoft R Open / Revolution R Enterprise
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
The free tier lets users have access to a variety of services free for 12 months with limited usage after making an Azure account.
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More Pricing Information
Community Pulse
Microsoft Azure
Microsoft R Open / Revolution R Enterprise
Features
Microsoft Azure
Microsoft R Open / Revolution R Enterprise
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
Microsoft Azure
8.5
27 Ratings
3% above category average
Microsoft R Open / Revolution R Enterprise
-
Ratings
Service-level Agreement (SLA) uptime
8.126 Ratings
00 Ratings
Dynamic scaling
8.725 Ratings
00 Ratings
Elastic load balancing
8.624 Ratings
00 Ratings
Pre-configured templates
8.225 Ratings
00 Ratings
Monitoring tools
8.326 Ratings
00 Ratings
Pre-defined machine images
8.424 Ratings
00 Ratings
Operating system support
9.026 Ratings
00 Ratings
Security controls
8.626 Ratings
00 Ratings
Automation
8.224 Ratings
00 Ratings
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Microsoft Azure
-
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 Product A and Product B
Microsoft Azure
-
Ratings
Microsoft R Open / Revolution R Enterprise
7.0
3 Ratings
19% 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 Product A and Product B
Microsoft Azure
-
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 Product A and Product B
Microsoft Azure
-
Ratings
Microsoft R Open / Revolution R Enterprise
6.0
3 Ratings
33% 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 Product A and Product B
Azure is particularly well suited for enterprise environments with existing Microsoft investments, those that require robust compliance features, and organizations that need hybrid cloud capabilities that bridge on-premises and cloud infrastructure. In my opinion, Azure is less appropriate for cost-sensitive startups or small businesses without dedicated cloud expertise and scenarios requiring edge computing use cases with limited connectivity. Azure offers comprehensive solutions for most business needs but can feel like there is a higher learning curve than other cloud-based providers, depending on the product and use case.
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.
Microsoft Azure is highly scalable and flexible. You can quickly scale up or down additional resources and computing power.
You have no longer upfront investments for hardware. You only pay for the use of your computing power, storage space, or services.
The uptime that can be achieved and guaranteed is very important for our company. This includes the rapid maintenance for security updates that are mostly carried out by Microsoft.
The wide range of capabilities of services that are possible in Microsoft Azure. You can practically put or create anything in Microsoft Azure.
The cost of resources is difficult to determine, technical documentation is frequently out of date, and documentation and mapping capabilities are lacking.
The documentation needs to be improved, and some advanced configuration options require research and experimentation.
Microsoft's licensing scheme is too complex for the average user, and Azure SQL syntax is too different from traditional SQL.
Moving to Azure was and still is an organizational strategy and not simply changing vendors. Our product roadmap revolved around Azure as we are in the business of humanitarian relief and Azure and Microsoft play an important part in quickly and efficiently serving all of the world. Migration and investment in Azure should be considered as an overall strategy of an organization and communicated companywide.
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.
As Microsoft Azure is [doing a] really good with PaaS. The need of a market is to have [a] combo of PaaS and IaaS. While AWS is making [an] exceptionally well blend of both of them, Azure needs to work more on DevOps and Automation stuff. Apart from that, I would recommend Azure as a great platform for cloud services as scale.
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.
We were running Windows Server and Active Directory, so [Microsoft] Azure was a seamless transition. We ran into a few, if any support issues, however, the availability of Microsoft Azure's support team was more than willing and able to guide us through the process. They even proposed solutions to issues we had not even thought of!
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.
As I have mentioned before the issue with my Oracle Mismatch Version issues that have put a delay on moving one of my platforms will justify my 7 rating.
As I continue to evaluate the "big three" cloud providers for our clients, I make the following distinctions, though this gap continues to close. AWS is more granular, and inherently powerful in the configuration options compared to [Microsoft] Azure. It is a "developer" platform for cloud. However, Azure PowerShell is helping close this gap. Google Cloud is the leading containerization platform, largely thanks to it building kubernetes from the ground up. Azure containerization is getting better at having the same storage/deployment options.
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.
For about 2 years we didn't have to do anything with our production VMs, the system ran without a hitch, which meant our engineers could focus on features rather than infrastructure.
DNS management was very easy in Azure, which made it easy to upgrade our cluster with zero downtime.
Azure Web UI was easy to work with and navigate, which meant our senior engineers and DevOps team could work with Azure without formal training.