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At a Glance
Market Segments
Small-Business (54.2% of reviews)
Small-Business (40.2% 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 watsonx.ai
Star Rating
(123)4.4 out of 5
Market Segments
Small-Business (40.2% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Free Trial is available
Learn more about IBM watsonx.aiSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that DataRobot excels in its Data Ingestion & Wrangling capabilities, scoring 8.2, which allows for efficient data preparation. In contrast, IBM watsonx.ai shines with a higher score of 9.0 in Ease of Deployment, indicating a smoother setup process according to reviewers.
- Reviewers mention that DataRobot's Model Registry feature is highly rated at 9.3, making it easier to manage and track models. However, users on G2 highlight that IBM watsonx.ai offers superior Monitoring capabilities with a score of 8.8, which is crucial for ongoing model performance evaluation.
- G2 users say that DataRobot's Quality of Support is rated at 7.9, which some find lacking compared to IBM watsonx.ai's impressive score of 8.8. This difference suggests that users may experience better assistance and resources with IBM's product.
- Users report that DataRobot has a strong focus on Structured Data with a score of 9.2, making it a preferred choice for users dealing primarily with structured datasets. Conversely, IBM watsonx.ai is noted for its versatility in Natural Language Processing, scoring 8.8, which appeals to users needing advanced text analysis features.
- Reviewers mention that DataRobot's Versioning feature is rated at 8.1, which is beneficial for tracking changes in models. However, IBM watsonx.ai's Scalability score of 9.0 indicates that it may better support growing data needs and larger deployments, according to user feedback.
- Users on G2 highlight that DataRobot's Ease of Use is rated at 8.5, which is favorable for new users. In contrast, IBM watsonx.ai's higher score of 9.1 in the same category suggests a more intuitive interface, making it easier for users to navigate and utilize its features effectively.
Pricing
Entry-Level Pricing
DataRobot
No pricing availableIBM watsonx.ai
No pricing availableFree Trial
DataRobot
No trial information availableIBM watsonx.ai
Free Trial is available
Ratings
Meets Requirements
8.8
23
8.8
78
Ease of Use
8.5
23
8.8
110
Ease of Setup
7.0
11
8.5
101
Ease of Admin
7.4
11
8.7
36
Quality of Support
7.9
22
8.8
77
Has the product been a good partner in doing business?
8.3
11
8.9
36
Product Direction (% positive)
8.4
22
9.9
80
Features by Category
Deployment
Not enough data
9.1
9
Not enough data
8.5
9
Not enough data
7.8
9
Not enough data
8.7
9
Not enough data
8.7
9
Deployment
Not enough data
9.3
9
Not enough data
8.7
9
Not enough data
8.3
9
Not enough data
8.9
9
Not enough data
9.1
9
Management
Not enough data
8.0
9
Not enough data
8.5
9
Not enough data
8.5
9
Not enough data
9.3
9
Operations
Not enough data
9.1
9
Not enough data
8.7
9
Not enough data
9.3
9
Management
Not enough data
8.5
9
Not enough data
9.0
8
Not enough data
8.5
8
Generative AI
Not enough data
9.1
9
Not enough data
9.3
9
System
Not enough data
8.2
31
Model Development
Not enough data
8.6
32
Not enough data
8.2
32
Not enough data
8.7
31
Not enough data
8.4
32
Model Development
Not enough data
8.5
32
Machine/Deep Learning Services
Not enough data
Feature Not Available
Not enough data
8.9
32
Not enough data
8.6
32
Not enough data
8.1
32
Machine/Deep Learning Services
Not enough data
8.5
32
Not enough data
8.8
32
Deployment
Not enough data
8.2
32
Not enough data
8.6
32
Not enough data
8.8
32
Generative AI
Not enough data
8.8
31
Not enough data
8.8
31
Not enough data
Feature Not Available
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 Type
Not enough data
8.8
13
Not enough data
Feature Not Available
Not enough data
8.5
12
Synthesis Type
Not enough data
9.0
12
Not enough data
9.2
12
Data Transformation
Not enough data
8.6
12
Not enough data
9.3
12
Not enough data
9.7
12
Not enough data
9.2
12
Not enough data
9.2
12
Scalability and Performance - Generative AI Infrastructure
Not enough data
9.4
8
Not enough data
9.0
8
Not enough data
9.4
8
Cost and Efficiency - Generative AI Infrastructure
Not enough data
7.9
8
Not enough data
8.6
7
Not enough data
8.3
7
Integration and Extensibility - Generative AI Infrastructure
Not enough data
9.5
7
Not enough data
8.6
7
Not enough data
8.8
7
Security and Compliance - Generative AI Infrastructure
Not enough data
8.3
7
Not enough data
8.8
7
Not enough data
8.6
7
Usability and Support - Generative AI Infrastructure
Not enough data
9.3
7
Not enough data
9.0
7
Content Generation - AI Content Creation Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management - AI Content Creation Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration - Machine Learning
Not enough data
9.0
21
Learning - Machine Learning
Not enough data
9.2
22
Not enough data
9.1
22
Not enough data
9.0
21
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
6
Not enough data
8.1
6
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
6
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
6
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
8.3
7
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
8.3
6
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
8.1
7
Not enough data
8.8
7
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
9.4
6
Not enough data
8.6
6
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.6
6
Not enough data
8.9
6
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.4
6
Not enough data
9.2
6
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
6
Customization - AI Agent Builders
Not enough data
9.0
8
Not enough data
9.2
8
Not enough data
9.0
7
Functionality - AI Agent Builders
Not enough data
8.6
7
Not enough data
9.2
8
Not enough data
9.3
7
Not enough data
8.8
7
Data and Analytics - AI Agent Builders
Not enough data
9.0
7
Not enough data
8.8
7
Not enough data
9.0
7
Integration - AI Agent Builders
Not enough data
9.2
8
Not enough data
9.0
7
Not enough data
9.0
7
Not enough data
8.6
7
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
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Analysis
Not enough data
Not enough data
Not enough data
Not enough data
Decision Making
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
Categories
Categories
Shared Categories
DataRobot and IBM watsonx.ai are categorized as Data Science and Machine Learning Platforms and Low-Code Machine Learning Platforms
Unique Categories
DataRobot is categorized as Predictive Analytics
IBM watsonx.ai is categorized as Synthetic Data, MLOps Platforms, Machine Learning, AI Content Creation Platforms, Generative AI Infrastructure, Large Language Model Operationalization (LLMOps), and AI Agent Builders
Reviews
Reviewers' Company Size
DataRobot
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
IBM watsonx.ai
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%
Information Technology and Services
18.8%
Computer Software
11.6%
Consulting
7.1%
Financial Services
6.3%
Banking
6.3%
Other
50.0%
Alternatives
Discussions
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
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
IBM watsonx.ai has no discussions with answers
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