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Compare Amazon SageMaker and DVC 
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At a Glance
Market Segments
Small-Business (33.3% of reviews)
Mid-Market (54.5% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Amazon SageMaker
Star Rating
(45)4.3 out of 5
Market Segments
Small-Business (33.3% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Amazon SageMakerDVC
Star Rating
(11)4.7 out of 5
Market Segments
Mid-Market (54.5% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about DVCSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Amazon SageMaker excels in ease of use with a score of 8.4, making it a preferred choice for those who prioritize a user-friendly interface, while DVC, with a score of 6.9, is noted for its steeper learning curve, which may require more technical expertise to navigate effectively.
- Reviewers mention that Amazon SageMaker's managed service deployment, rated at 9.5, provides a seamless experience for scaling applications, whereas DVC, with a score of 8.8, offers flexibility but may require more manual intervention for scaling operations.
- G2 users highlight that Amazon SageMaker's quality of support is rated at 8.7, indicating a strong customer service experience, while DVC's support, rated at 7.3, has been described as less responsive, which could impact users needing timely assistance.
- Users on G2 report that Amazon SageMaker's model training capabilities, rated at 8.9, are robust with pre-built algorithms that simplify the process, while DVC, also scoring 8.9, is praised for its versioning capabilities, allowing for better tracking of model changes, but lacks the same level of pre-built resources.
- Reviewers mention that Amazon SageMaker's deployment flexibility, with a language support score of 8.8, allows for a wide range of programming languages, making it accessible for diverse teams, while DVC's language support is slightly lower, which may limit its appeal to teams with specific language preferences.
- Users say that Amazon SageMaker's product direction, rated at 8.8, reflects a commitment to continuous improvement and innovation, while DVC's perfect score of 10.0 indicates a strong alignment with user needs and future developments, suggesting that it may be more adaptable to evolving market demands.
Pricing
Entry-Level Pricing
Amazon SageMaker
No pricing availableDVC
No pricing availableFree Trial
Amazon SageMaker
No trial information availableDVC
No trial information availableRatings
Meets Requirements
8.6
37
8.9
9
Ease of Use
8.4
38
6.9
9
Ease of Setup
8.5
25
Not enough data
Ease of Admin
8.4
20
Not enough data
Quality of Support
8.6
33
7.3
8
Has the product been a good partner in doing business?
9.2
20
Not enough data
Product Direction (% positive)
9.0
36
10.0
8
Features by Category
Deployment
Not enough data
9.0
5
Not enough data
9.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
9.0
7
Not enough data
8.8
7
Not enough data
9.0
7
Not enough data
7.6
7
Not enough data
7.5
6
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
7.7
5
Operations
Not enough data
8.1
7
Not enough data
6.4
6
Not enough data
6.9
6
Management
Not enough data
6.9
6
Not enough data
7.1
7
Not enough data
8.3
6
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
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
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 DVC 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
DVC has no unique categories
Reviews
Reviewers' Company Size
Amazon SageMaker
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
DVC
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%
Research
18.2%
Computer Software
18.2%
Consulting
9.1%
Oil & Energy
9.1%
Logistics and Supply Chain
9.1%
Other
36.4%
Alternatives
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
DVC has no discussions with answers
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