Compare Azure Machine Learning and KNIME 
At a Glance
Market Segments
Enterprise (38.8% of reviews)
Enterprise (47.8% of reviews)
Entry-Level Pricing
No pricing available
Free
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 LearningKNIME
Star Rating
(70)4.4 out of 5
Market Segments
Enterprise (47.8% of reviews)
Pros & Cons
Entry-Level Pricing
Free
Browse all 6 pricing plansAzure Machine Learning vs KNIME
When assessing the two solutions, reviewers found Azure Machine Learning easier to use and administer. Reviewers also felt that Azure Machine Learning was easier to do business with overall. However, reviewers felt that the products are equally easy to set up.
- Azure Machine Learning and KNIME both meet the requirements of our reviewers at a comparable rate.
- 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 KNIME.
Pricing
Entry-Level Pricing
Azure Machine Learning
No pricing availableKNIME
KNIME Analytics Platform
Free
A free and open source software that allows anyone, irrespective of experience levels, to make sense of data using visual workflows.
Download today at knime.com/downloads and use it free forever.
- Access data from any data source - your laptop, an application or a data warehouse
- Easily blend data of any size and any type - all file formats supported
- Aggregate, sort, filter, and join data on your device, in-database, or in distributed big data environments
Free Trial
Azure Machine Learning
No trial information availableKNIME
Free Trial is available
Ratings
Meets Requirements
8.5
81
8.5
63
Ease of Use
8.5
80
8.2
63
Ease of Setup
8.3
57
8.3
20
Ease of Admin
8.3
49
7.9
16
Quality of Support
8.6
74
8.2
55
Has the product been a good partner in doing business?
8.6
47
8.1
14
Product Direction (% positive)
9.0
80
8.7
63
Features by Category
Administration
Not enough data
8.3
24
Not enough data
8.7
26
Not enough data
8.6
25
Capabilities
Not enough data
8.6
26
Not enough data
8.4
23
Not enough data
8.6
23
Not enough data
7.9
21
Methodology
Not enough data
8.3
21
Not enough data
8.7
25
Not enough data
8.5
24
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
8.9
16
Model Development
8.6
51
8.3
15
8.9
54
9.0
15
8.3
53
8.2
15
8.7
52
8.2
14
Model Development
8.4
21
8.1
15
Machine/Deep Learning Services
8.1
45
7.5
10
7.9
45
8.3
13
7.8
38
7.9
11
8.2
42
7.4
11
Machine/Deep Learning Services
8.7
21
8.0
14
8.5
21
7.8
13
Deployment
8.8
50
8.2
14
8.7
51
8.6
14
8.9
51
8.4
15
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
Statistical Tool
Not enough data
8.0
37
Not enough data
8.2
42
Not enough data
8.2
40
Data Analysis
Not enough data
8.3
33
Not enough data
8.3
42
Decision Making
Not enough data
8.3
31
Not enough data
8.0
41
Not enough data
7.9
39
Not enough data
8.4
40
Generative AI
Not enough data
7.2
6
Not enough data
7.2
6
Categories
Categories
Shared Categories
Azure Machine Learning and KNIME are categorized as Data Science and Machine Learning Platforms and Low-Code Machine Learning Platforms
Unique Categories
Azure Machine Learning is categorized as MLOps Platforms, Large Language Model Operationalization (LLMOps), and Generative AI Infrastructure
KNIME is categorized as Predictive Analytics and Statistical Analysis
Reviews
Reviewers' Company Size
Azure Machine Learning
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
KNIME
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
29.0%
Higher Education
11.6%
Research
5.8%
Banking
4.3%
E-Learning
4.3%
Other
44.9%
Discussions
What is Azure Machine Learning Studio used for?
2 Comments
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
Is Knime easy to use?
1 Comment
GB
Not as easy as Alteryx but a lot of its components are customizable and it vastly extends the use cases that could be built with it. This trumps the easy to...Read more
KNIME has no more discussions with answers
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