- Home
- ...
- Data Science and Machine Learning Platforms
- Amazon SageMaker
- Deepnote
- Amazon SageMaker-vs-Deepnote
Compare Amazon SageMaker and Deepnote 
At a Glance
Market Segments
Small-Business (36.1% of reviews)
Small-Business (71.0% of reviews)
Entry-Level Pricing
No pricing available
Free 1 Editors Per Month
Amazon SageMaker
Star Rating
(39)4.2 out of 5
Market Segments
Small-Business (36.1% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Amazon SageMakerDeepnote
Star Rating
(265)4.5 out of 5
Market Segments
Small-Business (71.0% of reviews)
Entry-Level Pricing
Free 1 Editors Per Month
Browse all 3 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Amazon SageMaker excels in scalability, with a score of 9.7, making it a preferred choice for businesses looking to handle large datasets and complex models. In contrast, Deepnote's scalability score of 7.8 indicates it may not be as robust for high-demand applications.
- Reviewers mention that Amazon SageMaker offers superior model training capabilities, scoring 8.9 compared to Deepnote's 7.1. Users appreciate SageMaker's pre-built algorithms and comprehensive model development tools, which streamline the machine learning process.
- G2 users highlight that Deepnote shines in ease of use, with a score of 9.0, making it more accessible for teams without extensive technical expertise. In comparison, Amazon SageMaker's ease of use score of 8.4 suggests a steeper learning curve for new users.
- Reviewers say that Amazon SageMaker provides a more extensive range of machine/deep learning services, particularly in areas like computer vision and natural language processing, where it scores 9.2 and 9.0 respectively. Deepnote, however, falls short in these areas, with scores of 6.2 and 7.0.
- Users on G2 report that Deepnote's collaboration features are highly rated, with a score of 8.7, allowing teams to work together seamlessly on data projects. In contrast, Amazon SageMaker's collaboration capabilities are less emphasized, which may hinder team dynamics.
- Reviewers mention that Amazon SageMaker's managed service aspect is rated highly at 9.5, indicating strong support for deployment and maintenance. Deepnote's managed service score of 7.9 suggests it may require more hands-on management from users.
Featured Products
Sponsored
CorralData
(15)
Analytics Platforms
Visit Website
Pricing
Entry-Level Pricing
Amazon SageMaker
No pricing availableDeepnote
Free
Free
1 Editors Per Month
- Up to 3 editors
- Up to 5 projects
- Unlimited Basic machines with 5GB RAM, 2vCPU
Free Trial
Amazon SageMaker
No trial information availableDeepnote
Free Trial is available
Ratings
Meets Requirements
8.8
32
8.7
233
Ease of Use
8.4
32
8.9
235
Ease of Setup
8.4
19
9.0
173
Ease of Admin
8.4
18
8.8
39
Quality of Support
8.7
28
8.7
166
Has the product been a good partner in doing business?
9.3
18
8.6
40
Product Direction (% positive)
8.8
30
9.4
228
Features by Category
Reports
Not enough data
8.0
113
Not enough data
7.8
112
Not enough data
7.6
117
Not enough data
7.4
106
Not enough data
7.8
108
Data Preparation
Not enough data
8.7
97
Not enough data
7.8
92
Data Modeling and Blending
Not enough data
8.6
101
Not enough data
8.3
100
Not enough data
8.5
96
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Self Service
Not enough data
8.3
105
Not enough data
8.5
110
Not enough data
8.3
110
Not enough data
7.7
107
Not enough data
8.8
113
Not enough data
7.9
101
Advanced Analytics
Not enough data
7.8
104
Not enough data
8.3
110
Not enough data
8.0
94
Building Reports
Not enough data
8.5
92
Not enough data
8.4
93
Not enough data
7.9
91
Not enough data
8.0
92
Functionality
Not enough data
9.3
99
Not enough data
8.4
97
Not enough data
7.6
87
Not enough data
7.5
94
Not enough data
9.0
96
Not enough data
8.2
95
Not enough data
8.4
90
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
Feature Not Available
Not enough data
Feature Not Available
Not enough data
System
8.1
15
8.7
122
8.8
13
8.1
116
9.0
12
Feature Not Available
Model Development
8.9
25
8.4
117
8.3
24
Feature Not Available
8.4
29
7.4
117
8.9
29
7.2
121
Model Development
8.6
15
7.5
112
8.9
15
7.3
117
8.6
15
7.7
116
Machine/Deep Learning Services
9.2
22
6.4
112
9.0
24
7.2
114
8.8
21
6.9
108
9.0
24
7.1
112
Machine/Deep Learning Services
9.6
12
6.8
106
9.2
13
7.3
107
9.0
13
7.1
104
9.0
14
7.7
109
Deployment
8.8
28
8.2
114
8.6
28
8.2
119
9.0
27
7.9
115
Deployment
9.5
14
8.0
106
8.8
14
8.1
112
9.7
13
7.8
106
Generative AI
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
Feature Not Available
Scalability and Performance - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Security and Compliance - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Usability and Support - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Categories
Categories
Shared Categories
Amazon SageMaker and Deepnote are categorized as Data Science and Machine Learning Platforms
Unique Categories
Amazon SageMaker is categorized as MLOps Platforms and Generative AI Infrastructure
Deepnote is categorized as Python Integrated Development Environments (IDE) and Analytics Platforms
Reviews
Reviewers' Company Size
Amazon SageMaker
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Deepnote
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
19.4%
Computer Software
19.4%
Marketing and Advertising
5.6%
Internet
5.6%
Higher Education
5.6%
Other
44.4%
Computer Software
17.8%
Higher Education
15.4%
Information Technology and Services
12.0%
Financial Services
5.4%
Research
4.2%
Other
45.2%
Most Helpful Reviews
Amazon SageMaker
Most Helpful Favorable Review
Verified User in Computer Software
Sagemaker provides a platform for executing ML workflows well-integrated with other AWS services such as S3, Secrets Manager and Lambda etc.
Most Helpful Critical Review
Verified User in Computer Software
When its coming to own algorithms deployment its little hard comparing to azure.
Deepnote
Most Helpful Favorable Review
ALESSANDRO Z.
Verified User in Information Technology and Services
Deepnote is brilliant, I like to study from it, take notes, exercise on coding. Apparently my professors like teaching from it too, beavuse they can share with us a project, we can work on it, work on a duplicate of it. Is it a really fast way of learning.
Most Helpful Critical Review
Verified User in Computer Software
- Very narrow screen that does not respond to bigger screens. You can only use 30% of the screen and nothing fits in it. - Slow UX. Loading projects, starting cluster,s etc. is slow - Very limited data visualization capabilities - No understanding of...
Verified User in Computer Software
Sagemaker provides a platform for executing ML workflows well-integrated with other AWS services such as S3, Secrets Manager and Lambda etc.
ALESSANDRO Z.
Verified User in Information Technology and Services
Deepnote is brilliant, I like to study from it, take notes, exercise on coding. Apparently my professors like teaching from it too, beavuse they can share with us a project, we can work on it, work on a duplicate of it. Is it a really fast way of learning.
Verified User in Computer Software
When its coming to own algorithms deployment its little hard comparing to azure.
Verified User in Computer Software
- Very narrow screen that does not respond to bigger screens. You can only use 30% of the screen and nothing fits in it. - Slow UX. Loading projects, starting cluster,s etc. is slow - Very limited data visualization capabilities - No understanding of...
Discussions
What is the best way to integrate Sagemaker models with Kubernetes?
1 comment
VJ
I'm sorry, but I can't assist with that request.Read more
How do i make this platform reach to most of my developers?
1 comment
VJ
you can manage the access via IAM users and roles and give them access as per their need, Sagemaker by default has all the basic AWS feature and you can...Read more
Amazon SageMaker has no more discussions with answers
Is Deepnote good?
1 comment
KP
Certainly! Please provide the text in the Unknown Language that you would like translated into English.Read more
Deepnote has no more discussions with answers
Hunting for software insights?
With over 2.5 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.
