Feature differences for core service between deployment environments

The Cloud Pak for Data as a Service core services of Watson Studio, Watson Machine Learning, and Watson Knowledge Catalog have some feature differences between those services in other deployment environments.

The features listed are the ones available in the most comprehensive plan for each deployment environments.

Watson Studio

This table describes the feature differences between the Watson Studio service on multiple deployment environments. Watson Studio Local 2.1 has the same features as the service in Cloud Pak for Data 2.5.

* Indicates that the feature is limited or not available in some offering plans. See Watson Studio offering plans.

+ Indicates that the feature requires an additional service that might cost extra.

Feature Cloud Pak for Data
as a Service
Cloud Pak for Data
2.5
Cloud Pak for Data
3.0.1
Cloud Pak for Data
3.5
Watson Studio
Desktop
Collaboration in projects  
Jupyter notebooks
JupyterLab    
Scripts    
Data Refinery
Project import and export
Git integration    
Anaconda Repository integration     + +  
Master Data Management configuration +        
Crowd sourced annotation *        
RStudio + + +  
Remote data sources ✓, *
Personal credentials    
Upload data files
Link to data files        
Environment runtimes ✓, + ✓, + ✓, +  
GPU environments + + +  
Job scheduling  
SPSS Modeler flows + + +
Decision Optimization + + +  
Visual Recognition +        
Natural Language Classification +        
Dashboards + + + +  
Streams flows + + + +  
Hadoop integration   + + +  


Watson Machine Learning

This table describes the differences in features between the Watson Machine Learning service on multiple deployment environments. The Watson Machine Learning service on Watson Studio Local 2.1 has the same functionality as on Cloud Pak for Data 2.5.

+ indicates that the feature requires an additional service that might cost extra.

Feature Cloud Pak for Data
as a Service
Cloud Pak for Data
2.5
Cloud Pak for Data
3.0.1
Cloud Pak for Data
3.5
Watson Machine Learning
Server 2.x
Experiments  
AutoAI
Collaboration in deployment spaces
Deploy models
Deploy functions
Deploy scripts    
Deploy Shiny apps      
Continuous learning        
Federated learning      
Performance monitoring + + + +  
v4 APIs
Batch deployments
Online deployments
Virtual deployments (CoreML)
Evaluation jobs + + + +  
Deploy from projects  
Import and export deployment spaces    
Monitor deployments across spaces      
Watson Machine Learning Accelerator integration   + + +  


Watson Knowledge Catalog

This table describes the differences in features between the Watson Knowledge Catalog service multiple deployment environments.

* Indicates that the feature is limited or not available in some offering plans. See Watson Knowledge Catalog offering plans.

+ Indicates that the feature requires an additional service or an add-on that might cost extra.

Feature Cloud Pak for Data
as a Service
Cloud Pak for Data
2.5
Cloud Pak for Data
3.0.1
Cloud Pak for Data
3.5
AI powered search and recommendations
Rating and reviewing assets
Collaboration in projects
Data Refinery
Profiling of relational data
Remote data sources ✓, *
Personal credentials  
Custom asset types      
Metadata import in projects    
Advanced data curation  
Data quality analysis  
Categories with collaborator roles      
Automated term assignment  
Asset activities *
Operational data lineage  
Information assets view  
Predefined classifications
Custom classifications  
Predefined data classes
Custom data classes  
Business terms *
Policies *
Data protection rules *
Governance rules  
Reference data sets  
Governance artifact workflow  
Custom workflow configurations      
Import assets from Information Governance Catalog *