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Compare Amazon SageMaker and SAP HANA Cloud 
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At a Glance
Market Segments
Small-Business (33.3% of reviews)
Enterprise (63.3% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Amazon SageMaker
Star Rating
(46)4.2 out of 5
Market Segments
Small-Business (33.3% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Amazon SageMakerSAP HANA Cloud
Star Rating
(571)4.3 out of 5
Market Segments
Enterprise (63.3% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Free Trial is available
Learn more about SAP HANA CloudSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that SAP HANA Cloud excels in Database Management with a score of 8.9, while Amazon SageMaker, although strong, scores slightly lower at 8.6. Reviewers mention that SAP's robust management features make it a preferred choice for enterprises needing comprehensive database solutions.
- Reviewers mention that Amazon SageMaker shines in Model Development, particularly with its Pre-Built Algorithms scoring 8.6 and Model Training at 8.9. Users on G2 appreciate the ease of use and flexibility in developing machine learning models, making it ideal for small businesses.
- G2 users highlight that SAP HANA Cloud's Data Security features, scoring 8.7, provide a strong sense of protection for sensitive data, while Amazon SageMaker's security features, although good, score slightly lower at 8.6. Reviewers say that SAP's focus on enterprise-level security is a significant advantage.
- Users report that Amazon SageMaker offers superior Scalability with a score of 9.7, compared to SAP HANA Cloud's 9.0. Reviewers mention that SageMaker's ability to handle large-scale machine learning tasks efficiently is a key factor for businesses looking to grow.
- Reviewers mention that SAP HANA Cloud's Reports Interface is highly rated at 9.0, providing users with intuitive and visually appealing reporting capabilities. In contrast, Amazon SageMaker's reporting features, while functional, do not match the same level of user satisfaction, scoring 8.5.
- Users on G2 report that Amazon SageMaker's Ease of Setup is a standout feature, scoring 8.4, which is notably higher than SAP HANA Cloud's score of 7.7. Reviewers say that the straightforward setup process makes SageMaker an attractive option for users who want to get started quickly.
Pricing
Entry-Level Pricing
Amazon SageMaker
No pricing availableSAP HANA Cloud
No pricing availableFree Trial
Amazon SageMaker
No trial information availableSAP HANA Cloud
Free Trial is available
Ratings
Meets Requirements
8.6
37
8.7
351
Ease of Use
8.4
38
8.1
361
Ease of Setup
8.5
25
7.8
246
Ease of Admin
8.4
20
7.9
197
Quality of Support
8.6
33
8.1
335
Has the product been a good partner in doing business?
9.2
20
8.5
193
Product Direction (% positive)
9.0
36
8.6
318
Features by Category
Reports
Not enough data
8.5
30
Not enough data
8.4
29
Not enough data
8.9
29
Not enough data
8.6
26
Not enough data
9.0
29
Self Service
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
Advanced Analytics
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
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
Reports
Not enough data
8.5
30
Not enough data
8.4
29
Not enough data
8.9
29
Not enough data
8.6
26
Not enough data
9.0
29
Reports
Not enough data
8.6
22
Not enough data
8.5
22
Not enough data
8.0
22
Generative AI
Not enough data
6.2
19
Not enough data
6.2
19
Visualization
Not enough data
8.7
22
Not enough data
8.1
22
Not enough data
9.0
21
Not enough data
8.4
21
Data Updates
Not enough data
8.3
22
Not enough data
8.7
22
Collaboration
Not enough data
8.2
22
Not enough data
8.0
22
Not enough data
8.3
22
Data Updates
Not enough data
8.9
25
Not enough data
8.9
26
Not enough data
8.1
25
Cartography
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Analysis
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Reporting
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Administration
Not enough data
8.8
83
Not enough data
8.7
79
Not enough data
8.6
81
Federation
Not enough data
8.6
76
Not enough data
8.5
75
Not enough data
8.4
74
Not enough data
8.7
77
Transformation
Not enough data
8.7
82
Not enough data
8.8
84
Not enough data
8.7
82
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
8.2
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
Management
Not enough data
8.7
20
Not enough data
8.8
20
Not enough data
9.0
19
Not enough data
8.8
20
Not enough data
8.9
19
Maintenance
Not enough data
8.5
20
Not enough data
8.9
20
Not enough data
8.6
20
Security
Not enough data
8.8
20
Not enough data
8.6
20
Management
Not enough data
8.5
85
Not enough data
8.4
84
Not enough data
8.4
80
Not enough data
8.6
84
Support
Not enough data
8.3
84
Not enough data
8.6
85
Not enough data
8.3
86
Not enough data
Feature Not Available
Security
Not enough data
8.8
82
Not enough data
8.6
82
Not enough data
8.7
82
Not enough data
8.8
84
Performance
Not enough data
8.7
81
Not enough data
8.7
80
Not enough data
8.6
80
Not enough data
8.7
78
Not enough data
Feature Not Available
Database Features
Not enough data
8.7
210
Not enough data
8.6
212
Not enough data
8.5
213
Not enough data
8.6
211
Not enough data
8.7
211
Not enough data
8.2
202
Not enough data
8.3
197
Setup
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data
Not enough data
Not enough data
Not enough data
Not enough data
Analysis
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
Customization
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
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
Integration - Machine Learning
Not enough data
Not enough data
Learning - Machine Learning
Not enough data
Not enough data
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
Statistical Tool
Not enough data
8.2
10
Not enough data
8.2
10
Not enough data
8.8
10
Data Analysis
Not enough data
8.8
10
Not enough data
8.5
8
Decision Making
Not enough data
8.1
9
Not enough data
9.4
9
Not enough data
9.3
9
Not enough data
9.3
9
Generative AI
Not enough data
6.9
9
Not enough data
7.2
9
Configuration
Not enough data
8.7
82
Not enough data
8.5
78
Not enough data
8.7
80
Not enough data
8.2
74
Not enough data
8.7
77
Database Administration
Not enough data
8.5
78
Not enough data
8.3
77
Not enough data
8.4
78
Availability
Not enough data
8.7
80
Not enough data
8.5
78
Not enough data
8.6
76
Not enough data
8.6
75
Security
Not enough data
8.7
69
Not enough data
8.6
72
Not enough data
8.6
72
Data Management
Not enough data
8.6
74
Not enough data
8.6
73
Categories
Categories
Shared Categories
Amazon SageMaker and SAP HANA Cloud are categorized as MLOps Platforms and Data Science and Machine Learning Platforms
Unique Categories
Amazon SageMaker is categorized as Generative AI Infrastructure and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
Amazon SageMaker
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
SAP HANA Cloud
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
19.9%
Computer Software
8.1%
Retail
4.5%
Accounting
4.3%
Oil & Energy
3.9%
Other
59.3%
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
SAP HANA Vs Oracle
2 Comments
PB
HANA is in-memory database delivered with its appliance, can compress the data at its optimized size which helps to lower the size of DB to be used in...Read more
How is SAP HANA makes data processing and transactions very fast
2 Comments
SN
by minimizing the no. of business process steps by 30 to 40%Read more
HANA What is Next
1 Comment
PB
HANA what is next ?question is tricky, see HANA is a in memory DB with its certified appliance, a strong DB fighting against the traditional DBs like Oracle,...Read more
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