Compare Dataiku and Google Cloud AutoML 
At a Glance
Market Segments
Enterprise (61.7% of reviews)
Small-Business (45.5% of reviews)
Entry-Level Pricing
Free 3 Users
No pricing available
Dataiku
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 plansGoogle Cloud AutoML
Star Rating
(22)4.1 out of 5
Market Segments
Small-Business (45.5% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Google Cloud AutoMLSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Dataiku excels in user satisfaction, boasting a significantly higher overall score compared to Google Cloud AutoML. Users appreciate its intuitive graphical user interface, which allows for easy management of code and datasets, making the experience feel seamless and efficient.
- According to verified reviews, Dataiku's implementation process is praised for its quick onboarding, with users highlighting how easy it is to prototype and launch MVPs. In contrast, Google Cloud AutoML, while user-friendly, has received feedback indicating that it may not be as straightforward for those unfamiliar with machine learning.
- Reviewers mention that Dataiku's support quality stands out, with many users noting the helpfulness and responsiveness of the support team. This is a stark contrast to Google Cloud AutoML, where users have expressed some concerns about the support experience, indicating it could be improved.
- Users say that Dataiku is particularly well-suited for enterprise environments, with a majority of its reviews coming from larger organizations. This positions it as a robust choice for businesses looking for a comprehensive data science platform, while Google Cloud AutoML is more favored by small businesses, which may limit its appeal for larger enterprises.
- Reviewers highlight that Dataiku's ease of use is a significant advantage, with many finding it simple to navigate and integrate into their existing workflows. In comparison, Google Cloud AutoML, although intuitive, may require a bit more technical knowledge to fully leverage its capabilities, which could be a barrier for some users.
- According to recent user feedback, Dataiku's ability to adapt to various use cases is a strong point, with users noting its flexibility in handling different data types and projects. Google Cloud AutoML, while powerful, has been described as sometimes too generic for specific enterprise needs, which can limit its effectiveness in tailored applications.
Pricing
Entry-Level Pricing
Dataiku
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
Google Cloud AutoML
No pricing availableFree Trial
Dataiku
Free Trial is available
Google Cloud AutoML
No trial information availableRatings
Meets Requirements
8.7
171
8.6
14
Ease of Use
8.8
170
8.6
14
Ease of Setup
8.1
132
7.4
11
Ease of Admin
8.0
61
7.9
12
Quality of Support
8.6
156
7.5
14
Has the product been a good partner in doing business?
8.6
61
8.3
11
Product Direction (% positive)
9.0
167
8.9
11
Features by Category
Reports
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
Not enough data
Data Preparation
8.7
65
Not enough data
8.2
63
Not enough data
Data Modeling and Blending
8.6
62
Not enough data
8.6
62
Not enough data
8.7
62
Not enough data
Generative AI
7.9
50
Not enough data
8.0
50
Not enough data
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
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
Not enough data
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
8.4
74
Not enough data
7.8
75
Not enough data
8.0
74
Not enough data
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
8.5
91
Not enough data
8.6
88
Not enough data
7.7
85
Not enough data
8.1
89
Not enough data
Deployment
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
Not enough data
Deployment
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
Not enough data
Management
7.6
13
Not enough data
8.5
13
Not enough data
8.3
13
Not enough data
7.8
13
Not enough data
Operations
8.5
13
Not enough data
8.3
13
Not enough data
8.8
13
Not enough data
Management
7.5
12
Not enough data
8.5
13
Not enough data
7.9
13
Not enough data
Generative AI
8.3
6
Not enough data
8.3
6
Not enough data
System
8.6
75
Not enough data
Model Development
8.4
78
Not enough data
8.8
77
Not enough data
8.6
78
Not enough data
8.5
77
Not enough data
Model Development
8.5
77
Not enough data
Machine/Deep Learning Services
8.0
74
Not enough data
8.1
74
Not enough data
7.9
73
Not enough data
7.9
72
Not enough data
Machine/Deep Learning Services
7.7
68
Not enough data
7.9
69
Not enough data
Deployment
8.1
74
Not enough data
8.2
77
Not enough data
8.3
76
Not enough data
Generative AI
8.1
60
Not enough data
8.0
60
Not enough data
7.7
59
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
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
8.1
18
Not enough data
7.6
19
Not enough data
7.5
16
Not enough data
Cost and Efficiency - Generative AI Infrastructure
7.0
17
Not enough data
7.3
10
Not enough data
8.1
9
Not enough data
Integration and Extensibility - Generative AI Infrastructure
7.5
17
Not enough data
7.7
18
Not enough data
7.5
17
Not enough data
Security and Compliance - Generative AI Infrastructure
7.3
16
Not enough data
7.4
16
Not enough data
7.7
16
Not enough data
Usability and Support - Generative AI Infrastructure
7.3
17
Not enough data
7.1
16
Not enough data
Integration - Machine Learning
8.7
26
Not enough data
Learning - Machine Learning
8.3
27
Not enough data
7.9
28
Not enough data
8.0
28
Not enough data
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
7.5
11
Not enough data
Prompt Engineering - Large Language Model Operationalization (LLMOps)
8.3
11
Not enough data
7.9
11
Not enough data
Inference Optimization - Large Language Model Operationalization (LLMOps)
7.1
11
Not enough data
Model Garden - Large Language Model Operationalization (LLMOps)
7.7
11
Not enough data
Custom Training - Large Language Model Operationalization (LLMOps)
7.6
11
Not enough data
Application Development - Large Language Model Operationalization (LLMOps)
7.9
11
Not enough data
Model Deployment - Large Language Model Operationalization (LLMOps)
8.5
11
Not enough data
7.7
11
Not enough data
Guardrails - Large Language Model Operationalization (LLMOps)
6.8
11
Not enough data
6.7
11
Not enough data
Model Monitoring - Large Language Model Operationalization (LLMOps)
7.3
11
Not enough data
7.4
11
Not enough data
Security - Large Language Model Operationalization (LLMOps)
7.6
11
Not enough data
7.4
11
Not enough data
Gateways & Routers - Large Language Model Operationalization (LLMOps)
7.1
11
Not enough data
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
8.2
35
Not enough data
8.5
35
Not enough data
8.0
35
Not enough data
Data Analysis
8.5
37
Not enough data
8.8
37
Not enough data
Decision Making
8.6
35
Not enough data
7.9
36
Not enough data
7.8
35
Not enough data
8.6
36
Not enough data
Generative AI
8.6
20
Not enough data
8.3
20
Not enough data
Data Transformation
8.5
44
Not enough data
9.2
39
Not enough data
Connectivity
8.2
38
Not enough data
8.3
40
Not enough data
8.7
41
Not enough data
8.9
44
Not enough data
Operations
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
Not enough data
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
8.5
91
Not enough data
8.6
88
Not enough data
7.7
85
Not enough data
8.1
89
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
Categories
Categories
Shared Categories
Dataiku and Google Cloud AutoML are categorized as Low-Code Machine Learning Platforms and Data Science and Machine Learning Platforms
Unique Categories
Google Cloud AutoML has no unique categories
Reviews
Reviewers' Company Size
Dataiku
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Google Cloud AutoML
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
Financial Services
14.9%
Pharmaceuticals
7.4%
Retail
5.7%
Manufacturing
5.1%
Consulting
5.1%
Other
61.7%
Research
13.6%
Information Technology and Services
13.6%
Computer Software
9.1%
Accounting
4.5%
Consumer Goods
4.5%
Other
54.5%
Alternatives
Discussions
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
Google Cloud AutoML has no discussions with answers
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