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Compare Dataiku and python-recsys 
Featured Products
At a Glance
Market Segments
Enterprise (61.1% of reviews)
Enterprise (42.9% of reviews)
Entry-Level Pricing
Free 3 Users
No pricing available
Dataiku
Star Rating
(188)4.4 out of 5
Market Segments
Enterprise (61.1% of reviews)
Pros & Cons
Entry-Level Pricing
Free 3 Users
Free Trial is available
Browse all 3 pricing planspython-recsys
Star Rating
(14)4.5 out of 5
Market Segments
Enterprise (42.9% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about python-recsysSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Dataiku excels in user satisfaction, with a significantly higher overall score compared to python-recsys. Users appreciate its intuitive graphical user interface, which simplifies the management of code and datasets, making it a preferred choice for those looking to quickly prototype and launch their projects.
- According to verified reviews, Dataiku has a much larger user base, reflected in its total number of reviews. With 173 reviews compared to python-recsys's 14, potential buyers can feel more confident in the reliability of Dataiku's performance and user experiences.
- Users say that while Dataiku is praised for its ease of use, python-recsys shines in its open-source nature, allowing users to easily install and customize the tool. Reviewers highlight the coding experience as beneficial for learning machine learning concepts and constructing algorithms, which can be a significant advantage for developers looking to enhance their skills.
- Reviewers mention that Dataiku's support quality is commendable, although python-recsys users rate their support slightly higher. However, Dataiku's recent feedback emphasizes its role as a great partner in business, suggesting that users feel well-supported in their endeavors.
- According to recent user feedback, Dataiku's ability to integrate AI into tech spaces is a standout feature, making it a great choice for organizations looking to leverage machine learning. In contrast, python-recsys users appreciate its capacity to handle large datasets, which is crucial for data-intensive applications.
- G2 reviewers highlight that while Dataiku has a strong focus on enterprise solutions, python-recsys appeals to a niche audience with its open-source flexibility. This makes python-recsys a good option for smaller teams or individual developers who want to experiment and learn without the constraints of a commercial product.
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
python-recsys
No pricing availableFree Trial
Dataiku
Free Trial is available
python-recsys
No trial information availableRatings
Meets Requirements
8.7
171
8.5
12
Ease of Use
8.8
170
8.3
12
Ease of Setup
8.2
132
8.9
11
Ease of Admin
8.0
60
9.2
10
Quality of Support
8.6
155
8.7
9
Has the product been a good partner in doing business?
8.6
60
9.4
8
Product Direction (% positive)
9.0
167
6.1
12
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
8.2
19
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
7.6
11
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 python-recsys are categorized as Machine Learning
Unique Categories
Dataiku is categorized as Low-Code Machine Learning Platforms, AI Orchestration, Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, AWS Marketplace, MLOps Platforms, Big Data Analytics, Data Science and Machine Learning Platforms, Analytics Platforms, Predictive Analytics, and AI Agents For Business Operations
python-recsys has no unique categories
Reviews
Reviewers' Company Size
Dataiku
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
python-recsys
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%
Insurance
5.1%
Other
61.7%
Information Technology and Services
28.6%
Computer Software
14.3%
Transportation/Trucking/Railroad
7.1%
Telecommunications
7.1%
Program Development
7.1%
Other
35.7%
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
python-recsys has no discussions with answers
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