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Compare Azure Machine Learning and TensorFlow 
Featured Products
At a Glance
Market Segments
Enterprise (38.8% of reviews)
Small-Business (51.5% 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 LearningTensorFlow
Star Rating
(136)4.5 out of 5
Market Segments
Small-Business (51.5% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about TensorFlowSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that TensorFlow excels in user satisfaction, boasting a higher overall score compared to Azure Machine Learning. Users appreciate its capabilities for developing complex applications, such as face detection, highlighting its effectiveness in handling intricate neural network tasks.
- Users say that TensorFlow's recent activity indicates a vibrant community, with multiple reviews in the last 90 days, suggesting that it remains a popular choice among developers. In contrast, Azure Machine Learning has not received any recent reviews, which may raise concerns about its current user engagement.
- Reviewers mention that TensorFlow's ease of use is commendable, particularly for those familiar with machine learning concepts. Users have noted its efficiency in executing complex tasks, making it a preferred tool for advanced projects, while Azure Machine Learning is praised for its user-friendly interface, which is beneficial for less technical users.
- According to verified reviews, TensorFlow shines in model training and deep learning capabilities, with users highlighting its robust features for artificial neural networks. Azure Machine Learning, while also capable, is seen as slightly less powerful in these areas, with users noting it has predefined services that may limit customization.
- Users appreciate Azure Machine Learning for its predefined services that cater to business needs, making it easy to create experiments and deploy models. However, some users feel that the interface could be improved, whereas TensorFlow's flexibility allows for more tailored solutions, albeit with a steeper learning curve.
- Reviewers highlight that both platforms offer strong support, but TensorFlow's community-driven resources and documentation are particularly beneficial for troubleshooting and learning. Azure Machine Learning users also report good support, but the reliance on external resources for implementation can be a drawback for some.
Pricing
Entry-Level Pricing
Azure Machine Learning
No pricing availableTensorFlow
No pricing availableFree Trial
Azure Machine Learning
No trial information availableTensorFlow
No trial information availableRatings
Meets Requirements
8.5
81
9.1
119
Ease of Use
8.5
80
8.0
123
Ease of Setup
8.3
57
8.3
101
Ease of Admin
8.3
49
7.9
39
Quality of Support
8.6
74
8.7
106
Has the product been a good partner in doing business?
8.6
47
8.3
36
Product Direction (% positive)
9.0
80
9.2
117
Features by Category
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
8.6
70
Model Development
8.6
51
8.9
97
8.9
54
7.2
83
8.3
53
8.8
97
8.7
52
9.2
96
Model Development
8.4
21
9.0
69
Machine/Deep Learning Services
8.1
45
9.1
95
7.9
45
9.0
89
7.8
38
8.9
87
8.2
42
9.4
97
Machine/Deep Learning Services
8.7
21
8.7
64
8.5
21
9.2
68
Deployment
8.8
50
8.5
80
8.7
51
8.7
90
8.9
51
9.0
89
Generative AI
8.5
10
8.0
11
8.2
10
7.7
11
7.5
10
8.0
11
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
7.3
5
Not enough data
7.3
5
Not enough data
8.0
5
Not enough data
8.7
5
Not enough data
8.3
5
Not enough data
7.0
5
Not enough data
7.7
5
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
Categories
Categories
Shared Categories
Azure Machine Learning and TensorFlow 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
TensorFlow has no unique categories
Reviews
Reviewers' Company Size
Azure Machine Learning
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
TensorFlow
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%
Computer Software
27.3%
Information Technology and Services
19.7%
Research
7.6%
Computer & Network Security
4.5%
Higher Education
3.0%
Other
37.9%
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
What is TensorFlow and why it is used?
2 Comments
PS
TensorFlow is an open-source library that lets you generate various models AI/ML/DL models.Read more
TensorFlow has no more discussions with answers
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