Compare Azure Machine Learning and Dataiku 
At a Glance
Market Segments
Enterprise (38.8% of reviews)
Enterprise (61.7% of reviews)
Entry-Level Pricing
No pricing available
Free 3 Users
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 LearningDataiku
Star Rating
(189)4.4 out of 5
Market Segments
Enterprise (61.7% of reviews)
Pros & Cons
Entry-Level Pricing
Free 3 Users
Free Trial is available
Browse all 3 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Dataiku excels in user experience, with many praising its graphical user interface that simplifies managing code and datasets visually. Users find this feature particularly soothing and conducive to quick prototyping, making it a strong choice for teams looking to accelerate their MVP development.
- According to verified reviews, Azure Machine Learning is recognized for its ease of use, especially for non-technical users. Reviewers appreciate the platform's predefined services that cater to business needs, allowing for straightforward experiment creation and model deployment as a web service.
- Users say that Dataiku's implementation process is notably quick and intuitive, with many highlighting how easy it is to plug and play various components. This flexibility is a significant advantage for teams needing to adapt quickly to changing project requirements.
- Reviewers mention that while Azure Machine Learning offers a solid user experience, some find its interface could be improved. However, the platform compensates with a wealth of online resources that help users navigate implementation challenges, making it a viable option for those willing to invest time in learning.
- G2 reviewers highlight that Dataiku has a strong presence in the enterprise market, with a majority of its reviews coming from larger organizations. This suggests that it is well-suited for complex projects requiring robust data handling and collaboration features.
- Users report that Azure Machine Learning shines in scalability, with many noting its ability to handle larger datasets and more complex models effectively. This makes it a compelling choice for organizations anticipating growth and needing a platform that can scale with their needs.
Pricing
Entry-Level Pricing
Azure Machine Learning
No pricing availableDataiku
Install Dataiku on Your Infrastructure
Free
3 Users
Download Free Edition on Mac, Linux, or virtual machine | Collaborate with up to 3 users | Prepare data and build basic data projects and apps (no deployment, automation, governance)
- Visual Data Prep & AutoML
- Full Code (Python, R) Data Prep & ML
- The LLM Mesh
Free Trial
Azure Machine Learning
No trial information availableDataiku
Free Trial is available
Ratings
Meets Requirements
8.5
81
8.7
171
Ease of Use
8.5
80
8.8
170
Ease of Setup
8.3
57
8.1
132
Ease of Admin
8.3
49
8.0
61
Quality of Support
8.6
74
8.6
156
Has the product been a good partner in doing business?
8.6
47
8.6
61
Product Direction (% positive)
9.0
80
9.0
167
Features by Category
Reports
Not enough data
7.8
76
Not enough data
7.7
75
Not enough data
7.5
76
Not enough data
7.5
74
Not enough data
7.6
76
Data Preparation
Not enough data
8.7
65
Not enough data
8.2
63
Data Modeling and Blending
Not enough data
8.6
62
Not enough data
8.6
62
Not enough data
8.7
62
Generative AI
Not enough data
7.9
50
Not enough data
8.0
50
Agentic AI - Analytics 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
Self Service
Not enough data
8.2
75
Not enough data
8.6
74
Not enough data
8.4
74
Not enough data
7.9
74
Not enough data
8.7
74
Not enough data
8.1
74
Deployment & Integration - Analytics 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
Advanced Analytics
Not enough data
8.4
74
Not enough data
7.8
75
Not enough data
8.0
74
Performance & Scalability - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Advanced Analytics & Modeling - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI Capabilities - Analytics 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
Personalized Intelligence - Analytics Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Building Reports
Not enough data
8.5
91
Not enough data
8.6
88
Not enough data
7.7
85
Not enough data
8.1
89
Deployment
Not enough data
8.1
15
Not enough data
8.7
15
Not enough data
8.6
15
Not enough data
8.9
15
Not enough data
9.0
15
Deployment
Not enough data
7.8
12
Not enough data
8.5
13
Not enough data
8.5
13
Not enough data
8.8
13
Not enough data
8.8
13
Management
Not enough data
7.6
13
Not enough data
8.5
13
Not enough data
8.3
13
Not enough data
7.8
13
Operations
Not enough data
8.5
13
Not enough data
8.3
13
Not enough data
8.8
13
Management
Not enough data
7.5
12
Not enough data
8.5
13
Not enough data
7.9
13
Generative AI
Not enough data
8.3
6
Not enough data
8.3
6
System
8.6
22
8.6
75
Model Development
8.6
51
8.4
78
8.9
54
8.8
77
8.3
53
8.6
78
8.7
52
8.5
77
Model Development
8.4
21
8.5
77
Machine/Deep Learning Services
8.1
45
8.0
74
7.9
45
8.1
74
7.8
38
7.9
73
8.2
42
7.9
72
Machine/Deep Learning Services
8.7
21
7.7
68
8.5
21
7.9
69
Deployment
8.8
50
8.1
74
8.7
51
8.2
77
8.9
51
8.3
76
Generative AI
8.5
10
8.1
60
8.2
10
8.0
60
7.5
10
7.7
59
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
Responses
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Automation - AI Agents
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
Platform
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Autonomy - AI Agents
Not enough data
Not enough data
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
8.1
18
Not enough data
7.6
19
Not enough data
7.5
16
Cost and Efficiency - Generative AI Infrastructure
Not enough data
7.0
17
Not enough data
7.3
10
Not enough data
8.1
9
Integration and Extensibility - Generative AI Infrastructure
Not enough data
7.5
17
Not enough data
7.7
18
Not enough data
7.5
17
Security and Compliance - Generative AI Infrastructure
Not enough data
7.3
16
Not enough data
7.4
16
Not enough data
7.7
16
Usability and Support - Generative AI Infrastructure
Not enough data
7.3
17
Not enough data
7.1
16
Integration - Machine Learning
Not enough data
8.7
26
Learning - Machine Learning
Not enough data
8.3
27
Not enough data
7.9
28
Not enough data
8.0
28
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
7.5
11
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.3
11
Not enough data
7.9
11
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
7.1
11
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
7.7
11
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
7.6
11
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
7.9
11
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
8.5
11
Not enough data
7.7
11
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
6.8
11
Not enough data
6.7
11
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
7.3
11
Not enough data
7.4
11
Security - Large Language Model Operationalization (LLMOps)
Not enough data
7.6
11
Not enough data
7.4
11
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
7.1
11
Agentic AI - AWS Marketplace
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Workflow Design & Integration - AI Orchestration
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
Performance Optimization & Analytics - AI Orchestration
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
Governance & Compliance Controls - AI Orchestration
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
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
35
Not enough data
8.5
35
Not enough data
8.0
35
Data Analysis
Not enough data
8.5
37
Not enough data
8.8
37
Decision Making
Not enough data
8.6
35
Not enough data
7.9
36
Not enough data
7.8
35
Not enough data
8.6
36
Generative AI
Not enough data
8.6
20
Not enough data
8.3
20
Data Transformation
Not enough data
8.5
44
Not enough data
9.2
39
Connectivity
Not enough data
8.2
38
Not enough data
8.3
40
Not enough data
8.7
41
Not enough data
8.9
44
Operations
Not enough data
8.1
42
Not enough data
9.1
41
Not enough data
8.7
40
Not enough data
8.6
40
Not enough data
8.9
35
Agentic AI - AI Agents
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
Building Reports
Not enough data
8.5
91
Not enough data
8.6
88
Not enough data
7.7
85
Not enough data
8.1
89
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 Dataiku are categorized as MLOps Platforms, Large Language Model Operationalization (LLMOps), Data Science and Machine Learning Platforms, Generative AI Infrastructure, and Low-Code Machine Learning Platforms
Unique Categories
Azure Machine Learning has no unique categories
Dataiku is categorized as AI Orchestration, AWS Marketplace, Big Data Analytics, Machine Learning, Analytics Platforms, Predictive Analytics, and AI Agents For Business Operations
Reviews
Reviewers' Company Size
Azure Machine Learning
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Dataiku
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%
Financial Services
14.9%
Pharmaceuticals
7.4%
Retail
5.7%
Manufacturing
5.1%
Consulting
5.1%
Other
61.7%
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
Can I securely work on my sensitive data?
2 Comments
PB
Hi,
DSS is on-premise software but we also provide a Amazon image and Docker if desired. You can try DSS on your own computer for free by downloading the...Read more
What data visualization and reporting methods do you support?
2 Comments
Official Response from Dataiku
Dataiku supports a number of tools for engaging stakeholders and team members, including:
- 25 types of interactive charts
- Dashboards that allow you...Read more
Can I test Data Science Studio ?
1 Comment
PB
Hi,
First of all, thanks for your interest. You can try DSS out for free on Dataiku's website (www.dataiku.com/try). You can download the Community Edition...Read more
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