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 | Â | Â | + | + | Â |
Master Data Management configuration | + | Â | Â | Â | Â |
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 | + | Â | Â | Â | Â |
Natural Language Classification | + | Â | Â | Â | Â |
Dashboards | + | + | + | + | Â |
Streams flows | + | + | + | + | Â |
Hadoop integration | Â | + | + | + | Â |
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 | + | + | + | + | Â |
v4 APIs | ✓ | ✓ | ✓ | ✓ | ✓ |
Batch deployments | ✓ | ✓ | ✓ | ✓ | ✓ |
Online deployments | ✓ | ✓ | ✓ | ✓ | ✓ |
Virtual deployments (CoreML) | ✓ | ✓ | ✓ | ✓ | ✓ |
Evaluation jobs | + | + | + | + | Â |
Deploy from projects | ✓ | ✓ | ✓ | ✓ |  |
Import and export deployment spaces |  |  | ✓ | ✓ | ✓ |
Monitor deployments across spaces | ✓ |  |  | ✓ |  |
Watson Machine Learning Accelerator integration | Â | + | + | + | Â |
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 | ✓ * |  | ✓ | ✓ |