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Compare Dataiku and IBM Cloud Pak for Data 
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At a Glance
Market Segments
Enterprise (62.6% of reviews)
Enterprise (50.0% 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)
Pros & Cons
Entry-Level Pricing
Free 3 Users
Free Trial is available
Browse all 3 pricing plansIBM Cloud Pak for Data
Star Rating
(88)4.3 out of 5
Market Segments
Enterprise (50.0% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about IBM Cloud Pak for DataSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Dataiku excels in its user-friendly interface, particularly highlighting the "Drag and Drop" feature, which received a score of 8.8, making it easier for non-technical users to create data workflows.
- Reviewers mention that IBM Cloud Pak for Data shines in its "Managed Service" deployment option, scoring 9.3, which allows for seamless integration and management of data across various cloud environments.
- G2 users indicate that Dataiku's "Data Ingestion & Wrangling" capabilities are robust, scoring 8.4, but they also note that IBM Cloud Pak for Data outperforms in this area with a score of 9.5, making it a better choice for complex data preparation tasks.
- Users on G2 highlight that Dataiku's "Model Training" feature is highly rated at 9.0, but reviewers mention that IBM Cloud Pak for Data's overall model development process, including "Pre-Built Algorithms," is equally strong, scoring 9.1, providing flexibility for data scientists.
- Reviewers say that Dataiku's "Data Visualization" tools are rated at 7.5, which some users find limiting, while IBM Cloud Pak for Data's tools score significantly higher at 8.7, offering more advanced options for creating insightful visual reports.
- Users report that Dataiku's "Collaboration / Workflow" features are well-received with a score of 9.2, but they also mention that IBM Cloud Pak for Data's "User, Role, and Access Management" capabilities, scoring 8.4, provide a more secure and organized environment for team projects.
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
IBM Cloud Pak for Data
No pricing availableFree Trial
Dataiku
Free Trial is available
IBM Cloud Pak for Data
No trial information availableRatings
Meets Requirements
8.7
167
8.5
47
Ease of Use
8.7
166
8.1
47
Ease of Setup
8.1
128
7.2
26
Ease of Admin
8.0
60
7.6
27
Quality of Support
8.5
152
8.3
42
Has the product been a good partner in doing business?
8.6
60
8.1
25
Product Direction (% positive)
9.0
163
8.8
47
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
Customization
Not enough data
8.0
5
Not enough data
Not enough data
Not enough data
Not enough data
Infrastructure
Not enough data
Not enough data
Not enough data
9.0
5
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
Not enough data
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
Infrastructure Provision
Not enough data
7.7
8
Not enough data
8.1
7
Not enough data
7.9
7
Not enough data
8.3
6
Not enough data
8.5
8
Not enough data
7.9
8
Not enough data
8.3
8
Not enough data
8.3
7
Management
Not enough data
8.6
7
Not enough data
8.3
7
Not enough data
8.1
8
Functionality
Not enough data
8.3
8
System
8.6
75
9.5
11
Model Development
8.4
78
8.3
8
8.8
77
8.5
8
8.6
78
9.1
9
8.5
77
8.8
8
Model Development
8.5
77
8.5
12
Machine/Deep Learning Services
8.0
74
8.7
9
8.1
74
9.4
8
7.9
73
9.6
8
7.9
72
9.0
7
Machine/Deep Learning Services
7.7
68
9.2
8
7.9
69
9.3
7
Deployment
8.1
74
9.3
9
8.2
77
9.3
9
8.3
76
8.9
9
Generative AI
8.1
60
8.3
5
8.0
60
8.3
5
7.7
59
8.3
5
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
Data Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
8.3
5
Analytics
Not enough data
Not enough data
Security
Not enough data
9.0
5
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
Agentic AI - Data Fabric
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
8.3
5
8.5
35
8.8
8
8.0
35
8.6
7
Data Analysis
8.5
37
8.7
9
8.8
37
9.0
7
Decision Making
8.6
35
8.3
6
7.9
36
8.8
7
7.8
35
8.8
8
8.6
36
8.3
8
Generative AI
8.6
20
Not enough data
8.3
20
Not enough data
Data Transformation
8.5
44
8.5
27
|
Verified
9.2
39
9.1
15
|
Verified
Connectivity
8.2
38
8.0
23
|
Verified
8.3
40
8.6
22
|
Verified
8.7
41
8.1
25
|
Verified
8.9
44
8.7
24
|
Verified
Operations
8.1
42
8.7
26
|
Verified
9.1
41
8.9
25
|
Verified
8.7
40
8.4
23
|
Verified
8.6
40
8.8
24
|
Verified
8.9
35
8.7
13
|
Verified
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 IBM Cloud Pak for Data are categorized as Big Data Analytics, Generative AI Infrastructure, Data Science and Machine Learning Platforms, and Predictive Analytics
Unique Categories
Dataiku is categorized as Large Language Model Operationalization (LLMOps), Low-Code Machine Learning Platforms, AWS Marketplace, MLOps Platforms, Machine Learning, Analytics Platforms, and AI Orchestration
IBM Cloud Pak for Data is categorized as Data Fabric, Virtual Private Cloud (VPC), and Infrastructure as a Service (IaaS)
Reviews
Reviewers' Company Size
Dataiku
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM Cloud Pak for Data
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
12.9%
Information Technology and Services
8.6%
Banking
8.6%
Financial Services
5.7%
Education Management
5.7%
Other
58.6%
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
IBM Cloud Pak for Data has no discussions with answers
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