Compare Dataiku and python-recsys 
At a Glance
Market Segments
Enterprise (46.2% of reviews)
Enterprise (42.9% of reviews)
Entry-Level Pricing
Free 3 Users
No pricing available
Dataiku
Star Rating
(48)4.3 out of 5
Market Segments
Enterprise (46.2% of reviews)
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)
Entry-Level Pricing
No pricing available
Learn more about python-recsysSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Dataiku excels in its Data Ingestion & Wrangling capabilities, scoring 8.4, which allows for seamless integration of various data sources. In contrast, python-recsys, while effective, does not emphasize this feature as strongly, leading to a less robust experience in data preparation.
- Reviewers mention that Dataiku's Drag and Drop interface is highly intuitive, scoring 8.8, making it easier for users to build models without extensive coding knowledge. Python-recsys, however, has a lower score of 9.0 in this area, indicating a more flexible but potentially less user-friendly approach.
- G2 users highlight that python-recsys shines in Model Training, with a score of 9.0, which is on par with Dataiku. However, users on G2 note that Dataiku's pre-built algorithms (9.1) provide a more comprehensive starting point for users looking to implement machine learning quickly.
- Users say that Dataiku's Quality of Support is rated at 8.5, which is slightly lower than python-recsys at 8.7. Reviewers mention that python-recsys offers more responsive customer service, which can be crucial for businesses needing immediate assistance.
- Reviewers mention that Dataiku's Scalability is rated at 8.3, which is competitive, but python-recsys scores higher at 8.5, indicating better performance in handling larger datasets and more complex models as user needs grow.
- Users report that Dataiku's Governed Discovery feature scores an impressive 9.0, allowing for better data governance and compliance, while python-recsys lacks a comparable feature, which may be a drawback for enterprises focused on regulatory compliance.
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Pricing
Entry-Level Pricing
Dataiku
FREE EDITION | Install Dataiku on Your Infrastructure
Free
3 Users
Download 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)
- Collaboration Features (3 Users)
- Visual Data Prep & AutoML
- Full Code (Python, R) Data Prep & ML
python-recsys
No pricing availableFree Trial
Dataiku
Free Trial is available
python-recsys
No trial information availableRatings
Meets Requirements
8.8
36
8.5
12
Ease of Use
8.8
36
8.3
12
Ease of Setup
7.6
19
8.9
11
Ease of Admin
7.5
12
9.2
10
Quality of Support
8.5
31
8.7
9
Has the product been a good partner in doing business?
8.1
12
9.4
8
Product Direction (% positive)
9.0
34
6.1
12
Features by Category
Reports
7.9
7
Not enough data
8.3
7
Not enough data
7.3
8
Not enough data
8.1
7
Not enough data
7.9
8
Not enough data
Data Preparation
Not enough data
Not enough data
Not enough data
Not enough data
Data Modeling and Blending
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Self Service
8.8
7
Not enough data
9.3
7
Not enough data
9.3
7
Not enough data
8.1
7
Not enough data
9.2
8
Not enough data
8.3
8
Not enough data
Advanced Analytics
9.0
7
Not enough data
7.9
8
Not enough data
9.2
8
Not enough data
Building Reports
9.3
9
Not enough data
8.8
8
Not enough data
8.6
6
Not enough data
8.9
9
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
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
Feature Not Available
Not enough data
Feature Not Available
Not enough data
System
8.4
18
Not enough data
8.4
17
Not enough data
8.8
20
Not enough data
Model Development
8.8
17
Not enough data
9.0
17
Not enough data
9.1
18
Not enough data
9.0
19
Not enough data
Model Development
8.9
20
Not enough data
9.0
20
Not enough data
8.8
20
Not enough data
Machine/Deep Learning Services
8.4
15
Not enough data
8.1
15
Not enough data
8.3
14
Not enough data
8.5
14
Not enough data
Machine/Deep Learning Services
8.8
16
Not enough data
8.5
14
Not enough data
8.3
14
Not enough data
8.6
17
Not enough data
Deployment
7.9
16
Not enough data
8.5
18
Not enough data
8.3
17
Not enough data
Deployment
8.6
17
Not enough data
8.5
18
Not enough data
8.5
18
Not enough data
Generative AI
8.8
8
Not enough data
8.3
8
Not enough data
8.5
8
Not enough data
Scalability and Performance - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Security and Compliance - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Usability and Support - Generative AI Infrastructure
Feature Not Available
Not enough data
Feature Not Available
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
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
Not enough data
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Security - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Not enough data
Not enough data
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
Not enough data
Statistical Tool
Not enough data
Not enough data
9.7
5
Not enough data
Not enough data
Not enough data
Data Analysis
9.0
5
Not enough data
9.3
5
Not enough data
Decision Making
Not enough data
Not enough data
8.0
5
Not enough data
8.7
5
Not enough data
9.0
5
Not enough data
Generative AI
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Data Transformation
8.1
9
Not enough data
Not enough data
Not enough data
Connectivity
8.3
7
Not enough data
9.0
8
Not enough data
8.0
9
Not enough data
8.9
9
Not enough data
Operations
7.5
8
Not enough data
8.9
9
Not enough data
9.0
8
Not enough data
8.3
9
Not enough data
Not enough data
Not enough data
Building Reports
9.3
9
Not enough data
8.8
8
Not enough data
8.6
6
Not enough data
8.9
9
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
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
Information Technology and Services
17.9%
Computer Software
12.8%
Pharmaceuticals
7.7%
Consulting
5.1%
Retail
5.1%
Other
51.3%
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%
Most Helpful Reviews
Dataiku
Most Helpful Favorable Review
Verified User in Information Technology and Services
1.Dataiku is one place tool where we can do work with data like Data Preparation Data Exploration automated AI ...
Most Helpful Critical Review
Verified User in Machinery
Glorified excel, slow to use and often is not very customizable
python-recsys
Most Helpful Favorable Review
Verified User in Computer Software
Python-recsys is a powerful python library that consist in a implementation of a recommeder system. You can recommend an item providing a user-based o item-based mechanism. Some matrix decomposition algorithms are implemented, such as singular value...
Most Helpful Critical Review
Verified User in Government Administration
Lists can be confusing to create for those used to SAS
Verified User in Information Technology and Services
1.Dataiku is one place tool where we can do work with data like Data Preparation Data Exploration automated AI ...
Verified User in Computer Software
Python-recsys is a powerful python library that consist in a implementation of a recommeder system. You can recommend an item providing a user-based o item-based mechanism. Some matrix decomposition algorithms are implemented, such as singular value...
Verified User in Machinery
Glorified excel, slow to use and often is not very customizable
Verified User in Government Administration
Lists can be confusing to create for those used to SAS
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
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
How does Dataiku compare to competing products?
1 comment
Official Response from Dataiku
The best choice usually depends on your setup, needs, and use cases; that said, many of our customers switched to Dataiku because of the depth of our...Read more
python-recsys has no discussions with answers
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