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 in Cloud Pak for Data as a Service, in Cloud Pak for Data 2.5, in Cloud Pak for Data 3.0.1, and in Watson Studio Desktop. 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 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		 Watson Studio
Desktop
Collaboration in projects ✓ ✓ ✓  
Jupyter notebooks ✓ ✓ ✓ ✓
JupyterLab   ✓ ✓  
Scripts   ✓ ✓  
Data Refinery ✓ ✓ ✓ ✓
Project import and export ✓ ✓ ✓ ✓
Git integration   ✓ ✓  
Anaconda Repository integration     +  
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 Knowledge Catalog integration + ✓ ✓  


Watson Machine Learning

This table describes the differences in features between the Watson Machine Learning service on Cloud Pak for Data as a Service, Watson Machine Learning Server 1.x for Watson Studio Desktop, the Watson Machine Learning service for Cloud Pak for Data 2.5, and the Watson Machine Learning service for Cloud Pak for Data 3.0.1. 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.
* indicates that the feature is limited or not available in some offering plans. See Offering plans.

Feature Cloud Pak for Data
as a Service		 Cloud Pak for Data
2.5		 Cloud Pak for Data
3.0.1		 Watson Machine Learning
Server 1.x
Experiments ✓ ✓ ✓  
AutoAI ✓ ✓ ✓  
Collaboration in deployment spaces   ✓ ✓ ✓
Deploy models ✓ ✓ ✓ ✓
Deploy functions ✓ ✓ ✓ ✓
Deploy scripts     ✓  
Deploy Shiny apps     ✓  
Continuous learning ✓      
Performance monitoring ✓ ✓ ✓  
v4 APIs   ✓ ✓ ✓
Batch deployments ✓ ✓ ✓ ✓
Online deployments ✓ ✓ ✓ ✓
Virtual deployments ✓ ✓ ✓ ✓
Evaluation jobs ✓ ✓ ✓  
Deploy from projects ✓ ✓ ✓  
Import and export deployment spaces     ✓  
Watson Machine Learning Accelerator integration   + +  


Watson Knowledge Catalog

This table describes the differences in features between the Watson Knowledge Catalog service in Cloud Pak for Data as a Service, Watson Knowledge Catalog Lite On Prem, which is included with Watson Studio Local 2.1, the Watson Knowledge Catalog service on Cloud Pak for Data 2.5, and the Watson Knowledge Catalog service on Cloud Pak for Data 3.0.1.

* indicates that the feature is limited or not available in some offering plans. See 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		 Watson Studio
Local 2.1		 Cloud Pak for Data
2.5		 Cloud Pak for Data
3.0.1
Number of catalogs * 1 Unlimited Unlimited
Number of assets * 50 Unlimited Unlimited
Number of collaborators * 50 Unlimited Unlimited
AI powered search and recommendations ✓ ✓ ✓ ✓
Rating and reviewing assets ✓ ✓ ✓ ✓
Collaboration in projects ✓ ✓ ✓ ✓
Data Refinery ✓ ✓ ✓ ✓
Profiling of relational data ✓   ✓ ✓
Remote data sources * ✓ ✓ ✓
Personal credentials   ✓ ✓ ✓
Basic discovery of assets ✓   ✓ ✓
Advanced data curation     ✓ ✓
Data quality analysis     ✓ ✓
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     ✓ ✓
Custom attributes     ✓ ✓
Governance artifact workflow     ✓ ✓
Information Governance Catalog integration *     Â