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Compare Dataiku and machine-learning in Python 
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At a Glance
Market Segments
Enterprise (62.6% of reviews)
Enterprise (40.6% of reviews)
Entry-Level Pricing
Free 3 Users
No pricing available
Dataiku
Star Rating
(183)4.4 out of 5
Market Segments
Enterprise (62.6% of reviews)
Entry-Level Pricing
Free 3 Users
Free Trial is available
Browse all 3 pricing plansmachine-learning in Python
Star Rating
(35)4.7 out of 5
Market Segments
Enterprise (40.6% of reviews)
Entry-Level Pricing
No pricing available
Learn more about machine-learning in PythonSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Dataiku excels in its Data Preparation capabilities, particularly with its Drag and Drop interface, which simplifies the data wrangling process. In contrast, users mention that while machine-learning in Python offers flexibility, it requires more coding knowledge, making it less accessible for non-technical users.
- Reviewers mention that Dataiku's Model Development features, including Pre-Built Algorithms, provide a user-friendly experience for building models quickly. On the other hand, users on G2 highlight that machine-learning in Python shines in its Feature Engineering capabilities, allowing for more customized and complex model development.
- G2 users appreciate Dataiku's Collaboration / Workflow tools, which facilitate teamwork through shared projects and version control. Conversely, users report that machine-learning in Python lacks built-in collaboration features, often requiring additional tools to manage team workflows effectively.
- Reviewers say that Dataiku's Quality of Support is commendable, with a score of 8.5, indicating responsive customer service. In contrast, users mention that while machine-learning in Python has a strong community, the support can be inconsistent, as it largely depends on community forums and documentation.
- Users report that Dataiku's Deployment options, particularly its Managed Service, make it easier to implement models in production environments. In comparison, reviewers mention that machine-learning in Python offers more control over deployment but requires more technical expertise to set up and manage.
- Users on G2 highlight that Dataiku's Data Visualization tools, such as Dashboards, are intuitive and visually appealing, making it easier to present findings. Meanwhile, reviewers mention that while machine-learning in Python can produce high-quality visualizations, it often requires additional libraries and coding, which can be a barrier for some users.
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
machine-learning in Python
No pricing availableFree Trial
Dataiku
Free Trial is available
machine-learning in Python
No trial information availableRatings
Meets Requirements
8.7
167
9.0
26
Ease of Use
8.7
166
9.0
29
Ease of Setup
8.1
128
8.8
20
Ease of Admin
8.0
60
9.0
17
Quality of Support
8.5
152
8.4
26
Has the product been a good partner in doing business?
8.6
60
8.9
16
Product Direction (% positive)
9.0
163
10.0
24
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
Scalability and Performance - Generative AI Infrastructure
7.8
16
Not enough data
7.5
16
Not enough data
7.4
14
Not enough data
Cost and Efficiency - Generative AI Infrastructure
6.9
15
Not enough data
6.9
7
Not enough data
7.6
7
Not enough data
Integration and Extensibility - Generative AI Infrastructure
7.1
15
Not enough data
7.1
14
Not enough data
7.0
14
Not enough data
Security and Compliance - Generative AI Infrastructure
7.0
14
Not enough data
7.0
14
Not enough data
7.4
14
Not enough data
Usability and Support - Generative AI Infrastructure
7.0
15
Not enough data
6.7
14
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
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 machine-learning in Python are categorized as Machine Learning
Unique Categories
Dataiku is categorized as Large Language Model Operationalization (LLMOps), Low-Code Machine Learning Platforms, Big Data Analytics, Generative AI Infrastructure, AWS Marketplace, MLOps Platforms, Data Science and Machine Learning Platforms, Analytics Platforms, Predictive Analytics, and AI Orchestration
machine-learning in Python has no unique categories
Reviews
Reviewers' Company Size
Dataiku
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
machine-learning in Python
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
15.2%
Pharmaceuticals
7.6%
Retail
5.8%
Manufacturing
5.3%
Insurance
5.3%
Other
60.8%
Computer Software
25.0%
Information Technology and Services
15.6%
Research
12.5%
Higher Education
6.3%
Telecommunications
3.1%
Other
37.5%
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
Which Python version is best for machine learning?
2 Comments
SM
3.7 or later version is best to use this language.Read more
What is Python with machine learning?
1 Comment
SD
Firstly python is just a way to get machine learning things get done not inter related to machine learning. But using python in machine learning will help...Read more
machine-learning in Python has no more discussions with answers
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