Introducing G2.ai, the future of software buying.Try now
Compare Azure Machine Learning and IBM Watson Studio 
Featured Products
At a Glance
Market Segments
Enterprise (38.8% of reviews)
Enterprise (50.9% 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 LearningIBM Watson Studio
Star Rating
(166)4.2 out of 5
Market Segments
Enterprise (50.9% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about IBM Watson StudioAzure Machine Learning vs IBM Watson Studio
When assessing the two solutions, reviewers found Azure Machine Learning easier to use, set up, and administer. Reviewers also preferred doing business with Azure Machine Learning overall.
- Reviewers felt that Azure Machine Learning meets the needs of their business better than IBM Watson Studio.
- When comparing quality of ongoing product support, reviewers felt that Azure Machine Learning is the preferred option.
- For feature updates and roadmaps, our reviewers preferred the direction of Azure Machine Learning over IBM Watson Studio.
Pricing
Entry-Level Pricing
Azure Machine Learning
No pricing availableIBM Watson Studio
No pricing availableFree Trial
Azure Machine Learning
No trial information availableIBM Watson Studio
No trial information availableRatings
Meets Requirements
8.5
81
8.3
122
Ease of Use
8.5
80
8.0
123
Ease of Setup
8.3
57
7.6
101
Ease of Admin
8.3
49
7.8
95
Quality of Support
8.6
74
8.2
114
Has the product been a good partner in doing business?
8.6
47
8.0
94
Product Direction (% positive)
9.0
80
8.5
116
Features by Category
Data Source Access
Not enough data
9.0
13
Not enough data
9.3
12
Not enough data
9.2
14
Data Interaction
Not enough data
9.0
14
Not enough data
9.2
12
Not enough data
9.4
12
Not enough data
9.1
13
Not enough data
9.2
12
Not enough data
9.2
13
Not enough data
9.1
13
Not enough data
9.6
12
Data Exporting
Not enough data
9.4
12
Not enough data
9.2
12
Not enough data
9.2
12
Generative AI
Not enough data
Not enough data
Deployment
Not enough data
8.8
8
Not enough data
9.2
8
Not enough data
9.0
8
Not enough data
9.4
8
Not enough data
8.8
8
Deployment
Not enough data
9.0
8
Not enough data
8.8
8
Not enough data
8.8
8
Not enough data
9.4
8
Not enough data
9.2
8
Management
Not enough data
9.3
7
Not enough data
9.6
8
Not enough data
9.0
7
Not enough data
9.0
8
Operations
Not enough data
9.0
8
Not enough data
9.0
8
Not enough data
9.3
7
Management
Not enough data
9.5
7
Not enough data
9.4
8
Not enough data
8.8
7
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
System
8.6
22
9.1
13
Model Development
8.6
51
8.6
34
8.9
54
8.9
35
8.3
53
8.5
36
8.7
52
8.4
37
Model Development
8.4
21
9.4
13
Machine/Deep Learning Services
8.1
45
8.6
28
7.9
45
8.5
35
7.8
38
Feature Not Available
8.2
42
8.6
28
Machine/Deep Learning Services
8.7
21
8.9
12
8.5
21
9.0
12
Deployment
8.8
50
8.5
32
8.7
51
8.6
33
8.9
51
8.7
31
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
Setup
Not enough data
8.6
7
Not enough data
8.3
7
Not enough data
9.7
6
Data
Not enough data
8.6
7
Not enough data
8.6
7
Analysis
Not enough data
9.7
6
Not enough data
8.1
7
Not enough data
8.1
7
Not enough data
8.3
7
Not enough data
8.8
7
Not enough data
8.1
7
Not enough data
7.9
7
Customization
Not enough data
9.0
7
Not enough data
8.1
7
Not enough data
9.2
6
Generative AI
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
Statistical Tool
Not enough data
8.0
14
Not enough data
8.4
15
Not enough data
8.1
15
Data Analysis
Not enough data
8.7
15
Not enough data
9.0
14
Decision Making
Not enough data
8.6
14
Not enough data
8.6
15
Not enough data
8.3
13
Not enough data
8.7
14
Generative AI
Not enough data
9.3
5
Not enough data
8.3
5
Categories
Categories
Shared Categories
Azure Machine Learning and IBM Watson Studio are categorized as MLOps Platforms and Data Science and Machine Learning Platforms
Unique Categories
Azure Machine Learning is categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
Azure Machine Learning
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM Watson Studio
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%
Information Technology and Services
15.7%
Computer Software
13.2%
Telecommunications
8.2%
Banking
7.5%
Education Management
5.7%
Other
49.7%
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
IBM Watson Studio has no discussions with answers
Hunting for software insights?
With over 3 million reviews, we can provide the specific details that help you make an informed software buying decision for your business. Finding the right product is important, let us help.
