Selecting a deployment pattern for real-time data streaming and analytics systems

Real-time data streaming and analytics systems are typically deployed using one of two deployment patterns:

Selecting a deployment pattern is one of the most important decisions to make in designing a GIS system for your organization.

Perhaps the most critical factor in this decision will be aligning with your organization’s IT principles, guidelines, and comfort-level in supporting different deployment approaches. For example, some organizations may prefer to standardize on SaaS-based systems and solutions. Other organizations may prefer Windows or Linux-based deployment patterns.

Note:

The capabilities as well as the considerations differ between deployment patterns. Review the comparisons below, along with the deployment pattern pages for additional information.

For general information and considerations around these deployment approaches see the ArcGIS products and deployment options page of the ArcGIS overview.

Capability comparison

In addition to aligning with your IT principles, guidelines, and comfort-level, it’s also important to consider the capabilities of each deployment pattern in your decision-making process. The capabilities of a real-time data streaming and analytics system differ between deployment patterns. The following matrix compares the specific capabilities supported by each of the deployment patterns.

Capabilities used in a self-service mapping, analysis, and sharing system, but typically provided by other systems, such as basemaps, geocoding, and other location services provided by a location services system are not listed below. Learn more about related system patterns.

Capability SaaS Windows/Linux
Feed ingest1
Data ingest
Spatial joins and relationships
Pattern analysis
Proximity analysis
Summarization analysis  
Track analysis
Geofence analysis
Data management
Custom input connectors  
Custom analysis tools  
Custom output connectors  
Mapping and visualization
Data publishing and hosting
Feed publishing and hosting
Send and store messages2
Sharing3

Full support

Partial support

  1. Supported input connectors (feed types) differ between deployment patterns 

  2. Supported output connectors differ between deployment patterns 

  3. Sharing capabilities typically provided by another system pattern 

See the real-time data streaming and analytics system capabilities for more information on each row listed above. Additionally, each of the cells above is described in more detail in the real-time data streaming and analytics system deployment pattern pages.

The capabilities represented above reflect those available as of June, 2024.

General considerations

The considerations below aim to help align your organization’s business and IT needs with the appropriate real-time data streaming and analytics system deployment pattern. The information presented here is not meant to be exhaustive, but rather highlights key considerations for designing and implementing real-time data streaming and analytics systems.

Selecting a deployment pattern is one of the most important decisions to make in designing a GIS system for your organization. However, it is not the only one. There are many additional factors to take into consideration when designing your system, including areas like security, reliability, and integration. As such, consider the information provided here is not exhaustive. Review the architecture practices and pillars of the ArcGIS Well-Architected Framework, as well as product documentation, in detail as part of your design process.

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