Compare Azure Machine Learning and Microsoft SQL Server 
Featured Products
At a Glance
Market Segments
Enterprise (38.8% of reviews)
Enterprise (45.5% 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 LearningMicrosoft SQL Server
Star Rating
(2,261)4.4 out of 5
Market Segments
Enterprise (45.5% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Microsoft SQL ServerAzure Machine Learning vs Microsoft SQL Server
When assessing the two solutions, reviewers found Microsoft SQL Server easier to use. However, reviewers felt that Azure Machine Learning is easier to set up and do business with overall. Both products were equally easy to administer.
- Reviewers felt that Microsoft SQL Server meets the needs of their business better than Azure Machine Learning.
- 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 Microsoft SQL Server.
Pricing
Entry-Level Pricing
Azure Machine Learning
No pricing availableMicrosoft SQL Server
No pricing availableFree Trial
Azure Machine Learning
No trial information availableMicrosoft SQL Server
No trial information availableRatings
Meets Requirements
8.5
81
9.0
1,854
Ease of Use
8.5
80
8.6
1,870
Ease of Setup
8.3
57
8.1
992
Ease of Admin
8.3
49
8.3
950
Quality of Support
8.6
74
8.3
1,649
Has the product been a good partner in doing business?
8.6
47
8.4
900
Product Direction (% positive)
9.0
80
8.4
1,825
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
Not enough data
Model Development
8.6
51
Not enough data
8.9
54
Not enough data
8.3
53
Not enough data
8.7
52
Not enough data
Model Development
8.4
21
Not enough data
Machine/Deep Learning Services
8.1
45
Not enough data
7.9
45
Not enough data
7.8
38
Not enough data
8.2
42
Not enough data
Machine/Deep Learning Services
8.7
21
Not enough data
8.5
21
Not enough data
Deployment
8.8
50
Not enough data
8.7
51
Not enough data
8.9
51
Not enough data
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
Management
Not enough data
8.9
153
Not enough data
8.8
153
Not enough data
9.2
158
Not enough data
8.9
153
Not enough data
8.9
156
Maintenance
Not enough data
8.9
154
Not enough data
9.0
159
Not enough data
9.0
154
Security
Not enough data
8.9
153
Not enough data
9.1
155
Management
Not enough data
9.0
149
Not enough data
9.2
151
Not enough data
8.8
137
Not enough data
8.8
142
Support
Not enough data
8.6
145
Not enough data
9.0
149
Not enough data
8.6
144
Not enough data
8.4
151
Security
Not enough data
8.8
148
Not enough data
9.0
148
Not enough data
8.8
145
Not enough data
9.0
149
Performance
Not enough data
8.7
144
Not enough data
8.8
141
Not enough data
8.7
147
Not enough data
8.6
145
Not enough data
8.8
146
Database Features
Not enough data
8.9
1287
Not enough data
9.0
1291
Not enough data
8.9
1299
Not enough data
8.7
1266
Not enough data
8.8
1267
Not enough data
8.8
1271
Not enough data
9.1
1291
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
8.5
56
Not enough data
8.8
57
Not enough data
8.4
54
Integrations
Not enough data
7.8
45
Not enough data
8.2
45
Platform
Not enough data
8.2
50
Not enough data
8.5
53
Not enough data
8.2
45
Processing
Not enough data
8.5
52
Not enough data
8.5
55
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 Microsoft SQL Server share no categories
Unique Categories
Azure Machine Learning is categorized as MLOps Platforms, Large Language Model Operationalization (LLMOps), Data Science and Machine Learning Platforms, Generative AI Infrastructure, and Low-Code Machine Learning Platforms
Microsoft SQL Server is categorized as Relational Databases, Database Management Systems (DBMS), Big Data Processing and Distribution, and On-Premise Data Integration
Reviews
Reviewers' Company Size
Azure Machine Learning
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Microsoft SQL Server
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
24.1%
Computer Software
13.7%
Hospital & Health Care
5.4%
Financial Services
4.3%
Higher Education
2.9%
Other
49.6%
Alternatives
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
How could I make much easier the experience with the order of my database?
4 Comments
AF
You can create different tables with your employee information eg employee table, employee roles etc. Then you can create a single view that will pull data...Read more
What is the best way to save your queries?
4 Comments
CA
I recommend that you use the saved querys in plain text or .sql or txt format you can use the same sql server query creator or a notepad +++ tool, they are...Read more
How can I work on the same query if the connection is lost (timeout) and then I reconnect?
4 Comments
JE
When this happens to me in SQL Server Management Studio, I just have to type USE {your database name here} and then select only that statement and execute...Read more
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