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At a Glance
Market Segments
Mid-Market (39.1% of reviews)
Small-Business (40.5% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
Cloudera Data Engineering
Star Rating
(23)4.7 out of 5
Market Segments
Mid-Market (39.1% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Cloudera Data EngineeringIBM watsonx.ai
Star Rating
(122)4.4 out of 5
Market Segments
Small-Business (40.5% of reviews)
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 Cloudera Data Engineering excels in Data Ingestion & Wrangling with a score of 9.4, while IBM watsonx.ai falls short with a score of 8.2. Reviewers mention that Cloudera's robust capabilities in handling diverse data sources make it a preferred choice for data engineers.
- Reviewers mention that Cloudera Data Engineering offers superior Ease of Setup with a score of 9.7 compared to IBM watsonx.ai's 9.1. Users on G2 appreciate the straightforward installation process and quick onboarding experience provided by Cloudera.
- Users say that Cloudera's Quality of Support is highly rated at 9.3, while IBM watsonx.ai's support is rated lower at 8.8. Reviewers highlight Cloudera's responsive customer service and extensive documentation as key factors in their satisfaction.
- G2 users report that Cloudera Data Engineering shines in Scalability with a score of 9.0, whereas IBM watsonx.ai has a slightly lower score of 8.5. Users mention that Cloudera's architecture allows for seamless scaling as data needs grow.
- Reviewers mention that IBM watsonx.ai offers better Natural Language Processing capabilities, scoring 9.3 compared to Cloudera's 9.2. Users appreciate the advanced features in IBM's NLP tools, which enhance their AI applications.
- Users report that Cloudera Data Engineering provides a more flexible Framework Flexibility score of 8.1, while IBM watsonx.ai scores 8.3. Reviewers note that Cloudera's support for various frameworks allows for greater customization in data projects.
Pricing
Entry-Level Pricing
Cloudera Data Engineering
No pricing availableIBM watsonx.ai
No pricing availableFree Trial
Cloudera Data Engineering
No trial information availableIBM watsonx.ai
Free Trial is available
Ratings
Meets Requirements
9.2
23
8.8
77
Ease of Use
9.3
23
8.9
109
Ease of Setup
9.8
7
8.5
100
Ease of Admin
9.5
7
8.7
36
Quality of Support
9.2
22
8.8
76
Has the product been a good partner in doing business?
9.3
7
8.9
36
Product Direction (% positive)
10.0
23
9.9
79
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
9.5
16
8.2
31
Model Development
9.8
16
8.6
32
9.3
17
8.2
32
9.2
15
8.7
31
9.3
16
8.4
32
Model Development
9.2
15
8.5
32
Machine/Deep Learning Services
9.2
16
Feature Not Available
9.4
16
8.9
32
9.3
16
8.6
32
9.2
16
8.1
32
Machine/Deep Learning Services
9.6
15
8.5
32
9.6
14
8.8
32
Deployment
9.3
16
8.2
32
9.5
17
8.6
32
9.4
16
8.8
32
Generative AI
9.4
14
8.8
31
9.0
14
8.8
31
9.1
15
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
9.3
7
Not enough data
8.8
7
Not enough data
9.3
7
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.3
7
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
8.1
6
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
8.3
6
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
8.3
6
Not enough data
8.6
6
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
8.8
7
Not enough data
9.0
7
Not enough data
9.0
7
Functionality - AI Agent Builders
Not enough data
8.6
7
Not enough data
9.0
7
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
9.0
7
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
Categories
Categories
Shared Categories
Cloudera Data Engineering and IBM watsonx.ai are categorized as Data Science and Machine Learning Platforms
Unique Categories
Cloudera Data Engineering has no unique categories
IBM watsonx.ai is categorized as Synthetic Data, MLOps Platforms, Machine Learning, AI Content Creation Platforms, Generative AI Infrastructure, Large Language Model Operationalization (LLMOps), AI Agent Builders, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
Cloudera Data Engineering
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
Information Technology and Services
26.1%
Computer Software
26.1%
Consulting
13.0%
Banking
8.7%
Program Development
4.3%
Other
21.7%
Information Technology and Services
18.9%
Computer Software
11.7%
Consulting
7.2%
Banking
6.3%
Marketing and Advertising
5.4%
Other
50.5%
Alternatives
Discussions
Cloudera Data Engineering has no discussions with answers
IBM watsonx.ai has no discussions with answers
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