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Compare Azure Machine Learning and Posit 
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At a Glance
Market Segments
Enterprise (38.8% of reviews)
Enterprise (48.6% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Azure Machine Learning
Star Rating
(88)4.3 out of 5
Market Segments
Enterprise (38.8% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Azure Machine LearningPosit
Star Rating
(562)4.5 out of 5
Market Segments
Enterprise (48.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about PositSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Posit excels in Data Ingestion & Wrangling with a score of 9.1, while Azure Machine Learning received a lower score of 8.7, indicating that Posit may offer more robust tools for preparing data for analysis.
- Reviewers mention that Azure Machine Learning shines in Model Training, scoring 8.8 compared to Posit's 8.9, suggesting that Azure provides a slightly more efficient environment for training machine learning models.
- G2 users highlight that Posit has a better Graphs and Charts interface with a score of 8.8, while Azure Machine Learning's score in this area is not specified, indicating that Posit may offer superior visualization capabilities for data analysis.
- Users on G2 report that Azure Machine Learning has a higher score in Scalability (8.9) compared to Posit (8.6), suggesting that Azure may be better suited for larger-scale deployments and handling increased workloads.
- Reviewers mention that Posit has a strong focus on Collaboration with a score of 8.1, while Azure Machine Learning's score in this area is not specified, indicating that Posit may provide better tools for team collaboration during projects.
- Users say that Azure Machine Learning offers better Quality of Support with a score of 8.6, compared to Posit's 8.1, suggesting that Azure may provide more effective customer service and support resources for users.
Pricing
Entry-Level Pricing
Azure Machine Learning
No pricing availablePosit
No pricing availableFree Trial
Azure Machine Learning
No trial information availablePosit
Free Trial is available
Ratings
Meets Requirements
8.5
81
9.1
496
Ease of Use
8.5
80
8.3
496
Ease of Setup
8.3
57
8.8
106
Ease of Admin
8.3
49
8.3
90
Quality of Support
8.6
74
8.1
403
Has the product been a good partner in doing business?
8.6
47
8.5
81
Product Direction (% positive)
9.0
80
8.5
488
Features by Category
Administration
Not enough data
8.7
76
Not enough data
9.2
82
Not enough data
8.2
76
Capabilities
Not enough data
9.0
89
Not enough data
8.9
67
Not enough data
8.9
55
Not enough data
8.8
59
Methodology
Not enough data
9.1
77
Not enough data
9.5
85
Not enough data
9.3
82
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Operations
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
8.6
22
9.1
25
Model Development
8.6
51
8.8
19
8.9
54
7.8
21
8.3
53
8.3
21
8.7
52
9.0
21
Model Development
8.4
21
9.0
20
Machine/Deep Learning Services
8.1
45
8.6
15
7.9
45
8.5
14
7.8
38
8.7
13
8.2
42
7.6
17
Machine/Deep Learning Services
8.7
21
8.6
17
8.5
21
9.1
18
Deployment
8.8
50
8.4
19
8.7
51
8.9
18
8.9
51
8.7
19
Generative AI
8.5
10
Not enough data
8.2
10
Not enough data
7.5
10
Not enough data
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Scalability and Performance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security and Compliance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Usability and Support - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
Not enough data
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Security - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Database
Not enough data
9.0
8
Not enough data
9.0
7
Not enough data
8.6
7
Integrations
Not enough data
8.3
5
Not enough data
8.3
6
Platform
Not enough data
7.9
8
Not enough data
8.7
10
Not enough data
8.3
6
Processing
Not enough data
8.3
5
Not enough data
8.1
8
Building Reports
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Azure Machine Learning and Posit are categorized as Data Science and Machine Learning Platforms
Unique Categories
Azure Machine Learning is categorized as MLOps Platforms, Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, and Low-Code Machine Learning Platforms
Posit is categorized as Statistical Analysis and Big Data Processing and Distribution
Reviews
Reviewers' Company Size
Azure Machine Learning
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Posit
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
28.2%
Computer Software
14.1%
Management Consulting
8.2%
Education Management
5.9%
Higher Education
4.7%
Other
38.8%
Higher Education
19.1%
Information Technology and Services
12.6%
Research
11.2%
Computer Software
8.7%
Education Management
5.6%
Other
42.8%
Alternatives
Discussions
What is Azure Machine Learning Studio used for?
1 Comment
AR
In short, to build, deploy, and manage high-quality models faster and with confidence.Read more
Azure Machine Learning has no more discussions with answers
Can we save our process if we don't save a project?
2 Comments
SL
There are many ways to save results as an R script runs, take a look at the R saveRDS function as one example.
For questions like this about R a great...Read more
What is the best way to run R code within a VBA routine?
1 Comment
PB
I ran into same kind of problems. Then I discovered PowerBI.
With PowerBI, and the help of PowerQuery, I'm getting rid of all VbA engines to process...Read more
Which software is used for R programming?
1 Comment
SH
RStudio is the most popular IDE for running R programs and has a free license. The official R software environment is an open-source free software...Read more
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