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Compare DataRobot and IBM Cloud Pak for Data 
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At a Glance
Market Segments
Small-Business (54.2% of reviews)
Enterprise (50.0% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
DataRobot
Star Rating
(26)4.4 out of 5
Market Segments
Small-Business (54.2% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about DataRobotIBM 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 DataRobot excels in Data Ingestion & Wrangling with a score of 9.5, making it a preferred choice for those needing efficient data preparation. In contrast, IBM Cloud Pak for Data, while strong, does not match this level of performance in this area.
- Reviewers mention that DataRobot's Pre-Built Algorithms score of 9.1 is a significant advantage, allowing users to quickly implement machine learning models. IBM Cloud Pak for Data, with a score of 7.8 in the same category, may require more customization and development time.
- G2 users highlight that DataRobot's Real-Time Analytics feature, rated at 8.5, provides timely insights, which is crucial for businesses needing immediate data-driven decisions. IBM Cloud Pak for Data, while capable, does not offer the same level of immediacy in analytics.
- Users on G2 report that DataRobot's Ease of Use rating of 8.5 makes it more accessible for teams without extensive technical expertise, whereas IBM Cloud Pak for Data's score of 8.1 indicates a steeper learning curve for new users.
- Reviewers mention that IBM Cloud Pak for Data shines in Quality of Support with a score of 8.3, which is higher than DataRobot's 7.9. This suggests that users may find more reliable assistance when facing challenges with IBM's platform.
- Users say that DataRobot's Customization capabilities, particularly in Custom VMs, are rated at 8.0, allowing for tailored solutions. In comparison, IBM Cloud Pak for Data offers a more rigid structure, which may limit flexibility for some users.
Pricing
Entry-Level Pricing
DataRobot
No pricing availableIBM Cloud Pak for Data
No pricing availableFree Trial
DataRobot
No trial information availableIBM Cloud Pak for Data
No trial information availableRatings
Meets Requirements
8.8
23
8.5
47
Ease of Use
8.5
23
8.1
47
Ease of Setup
7.0
11
7.2
26
Ease of Admin
7.4
11
7.6
27
Quality of Support
7.9
22
8.3
42
Has the product been a good partner in doing business?
8.3
11
8.1
25
Product Direction (% positive)
8.4
22
8.8
47
Features by Category
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
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
Not enough data
9.5
11
Model Development
Not enough data
8.3
8
Not enough data
8.5
8
Not enough data
9.1
9
Not enough data
8.8
8
Model Development
Not enough data
8.5
12
Machine/Deep Learning Services
Not enough data
8.7
9
Not enough data
9.4
8
Not enough data
9.6
8
Not enough data
9.0
7
Machine/Deep Learning Services
Not enough data
9.2
8
Not enough data
9.3
7
Deployment
Not enough data
9.3
9
Not enough data
9.3
9
Not enough data
8.9
9
Generative AI
Not enough data
8.3
5
Not enough data
8.3
5
Not enough data
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
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Cost and Efficiency - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration and Extensibility - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security and Compliance - Generative AI Infrastructure
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Usability and Support - Generative AI Infrastructure
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
Not enough data
8.3
5
Not enough data
8.8
8
Not enough data
8.6
7
Data Analysis
Not enough data
8.7
9
Not enough data
9.0
7
Decision Making
Not enough data
8.3
6
Not enough data
8.8
7
Not enough data
8.8
8
Not enough data
8.3
8
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Data Transformation
Not enough data
8.5
27
|
Verified
Not enough data
9.1
15
|
Verified
Connectivity
Not enough data
8.0
23
|
Verified
Not enough data
8.6
22
|
Verified
Not enough data
8.1
25
|
Verified
Not enough data
8.7
24
|
Verified
Operations
Not enough data
8.7
26
|
Verified
Not enough data
8.9
25
|
Verified
Not enough data
8.4
23
|
Verified
Not enough data
8.8
24
|
Verified
Not enough data
8.7
13
|
Verified
Building Reports
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
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
DataRobot and IBM Cloud Pak for Data are categorized as Data Science and Machine Learning Platforms and Predictive Analytics
Unique Categories
DataRobot is categorized as Low-Code Machine Learning Platforms
IBM Cloud Pak for Data is categorized as Data Fabric, Virtual Private Cloud (VPC), Big Data Analytics, Infrastructure as a Service (IaaS), and Generative AI Infrastructure
Reviews
Reviewers' Company Size
DataRobot
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
Computer Software
20.8%
Information Technology and Services
12.5%
Telecommunications
8.3%
Manufacturing
4.2%
Retail
4.2%
Other
50.0%
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
How much does using Algorithmia cost?
1 Comment
CP
You can get started on Algorithmia Teams for as little as $299/month. Go to teams.algorithmia.com and sign up now!Read more
I found a bug in an algorithm or it's not producing the expected results, what can I do?
1 Comment
CP
If you are an Algorithmia Enterprise user, contact your account team for an immediate response.
For Teams, while you are logged in to the platform, you...Read more
Can I use external libraries with my algorithms?
1 Comment
CP
Yes, you can. Algorithmia has complete package management capabilities built in to the platform. Read more
IBM Cloud Pak for Data has no discussions with answers
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