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Compare Amazon SageMaker and V7 Darwin 
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At a Glance
Market Segments
Small-Business (33.3% of reviews)
Small-Business (55.8% of reviews)
Entry-Level Pricing
No pricing available
Free
Amazon SageMaker
Star Rating
(45)4.3 out of 5
Market Segments
Small-Business (33.3% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Amazon SageMakerV7 Darwin
Star Rating
(54)4.8 out of 5
Market Segments
Small-Business (55.8% of reviews)
Entry-Level Pricing
Free
Browse all 4 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Amazon SageMaker excels in its Model Training Efficiency with a score of 8.9, while V7 shines with a perfect score of 10.0, indicating that V7 offers superior tools for optimizing model training processes.
- Reviewers mention that V7's Pre-Built Algorithms feature is highly praised, achieving a perfect score of 10.0, whereas Amazon SageMaker's score of 8.4 suggests it may not provide as extensive a library of pre-built solutions, which can be crucial for rapid deployment.
- G2 users highlight that V7's Collaboration tools are top-notch, scoring a perfect 10.0, making it easier for teams to work together on projects, while Amazon SageMaker's collaboration features are less emphasized, scoring lower at 9.3.
- Users on G2 report that Amazon SageMaker's Quality of Support is commendable with a score of 8.7, but V7 outperforms it with a score of 9.6, indicating that V7 may provide more responsive and effective customer service.
- Reviewers mention that V7's Human-in-the-Loop capabilities score 9.4, which enhances the model training process by incorporating human feedback, while Amazon SageMaker's offerings in this area are less robust, reflecting a potential gap in user engagement.
- Users say that V7's Scalability is exceptional, achieving a perfect score of 10.0, which is crucial for businesses looking to grow, while Amazon SageMaker also scores well at 9.8, but may not match the flexibility and performance of V7 in rapidly scaling applications.
Pricing
Entry-Level Pricing
Amazon SageMaker
No pricing availableV7 Darwin
Free Plan
Free
Try out the core functionalities and set up your workflow for free.
- 1 Workspace
- 10 User Licenses
- 3 Integrated Models
Free Trial
Amazon SageMaker
No trial information availableV7 Darwin
Free Trial is available
Ratings
Meets Requirements
8.6
37
9.5
38
Ease of Use
8.4
38
9.5
38
Ease of Setup
8.5
25
9.5
17
Ease of Admin
8.4
20
9.4
15
Quality of Support
8.6
33
9.6
36
Has the product been a good partner in doing business?
9.2
20
9.9
14
Product Direction (% positive)
9.0
36
9.6
32
Features by Category
Deployment
Not enough data
Not enough data
Not enough data
9.4
6
Not enough data
9.7
5
Not enough data
9.0
7
Not enough data
9.8
7
Deployment
Not enough data
Not enough data
Not enough data
9.3
5
Not enough data
9.7
6
Not enough data
9.2
6
Not enough data
9.8
7
Management
Not enough data
9.3
5
Not enough data
10.0
6
Not enough data
Not enough data
Not enough data
Not enough data
Operations
Not enough data
9.7
6
Not enough data
Not enough data
Not enough data
10.0
6
Management
Not enough data
10.0
5
Not enough data
9.7
5
Not enough data
9.3
5
Generative AI
Not enough data
Feature Not Available
Not enough data
Feature Not Available
System
8.2
19
Not enough data
Model Development
8.7
29
Not enough data
8.2
28
Not enough data
8.3
33
Not enough data
8.9
33
Not enough data
Model Development
8.4
19
Not enough data
Machine/Deep Learning Services
8.9
26
Not enough data
9.1
28
Not enough data
8.9
25
Not enough data
9.0
28
Not enough data
Machine/Deep Learning Services
9.2
17
Not enough data
9.2
18
Not enough data
Deployment
8.6
32
Not enough data
8.6
32
Not enough data
9.0
31
Not enough data
Generative AI
8.6
6
Not enough data
9.2
6
Not enough data
8.3
5
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
Quality
Not enough data
9.4
21
Not enough data
9.5
24
Not enough data
9.4
21
Not enough data
9.3
22
Automation
Not enough data
9.4
16
Not enough data
9.4
14
Image Annotation
Not enough data
9.3
27
Not enough data
9.4
24
Not enough data
9.1
17
Not enough data
9.2
18
Natural Language Annotation
Not enough data
9.1
13
Not enough data
8.5
9
Not enough data
9.0
10
Speech Annotation
Not enough data
7.7
8
Not enough data
7.5
8
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
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
Amazon SageMaker and V7 Darwin are categorized as MLOps Platforms
Unique Categories
Amazon SageMaker is categorized as Data Science and Machine Learning Platforms, Generative AI Infrastructure, and Low-Code Machine Learning Platforms
V7 Darwin is categorized as Data Labeling
Reviews
Reviewers' Company Size
Amazon SageMaker
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
V7 Darwin
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
19.0%
Computer Software
16.7%
Marketing and Advertising
4.8%
Internet
4.8%
Hospital & Health Care
4.8%
Other
50.0%
Information Technology and Services
25.0%
Computer Software
19.2%
Research
7.7%
Hospital & Health Care
5.8%
Industrial Automation
3.8%
Other
38.5%
Discussions
What is the best way to integrate Sagemaker models with Kubernetes?
1 Comment
VJ
https://aws.amazon.com/blogs/machine-learning/introducing-amazon-sagemaker-operators-for-kubernetes/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
V7 Darwin has no discussions with answers
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