Designing data patterns on the edge
As data flows securely from different sensors/actuators on the edge to the gateway or cloud over different protocols or channels, it is necessary for it to be safely stored, processed, and cataloged for further consumption. Therefore, any IoT data architecture needs to take into consideration the data models (as explained earlier), data storage, data flow patterns, and anti-patterns, which will be covered in this section. Let's start with data storage.
Data storage
Big data solutions on the cloud are designed to reliably store terabytes, petabytes, or exabytes of data and can scale across multiple geographic locations globally to provide high availability and redundancy for businesses to meet their Recovery Time Objective (RTO) and Recovery Point Objective (RPO). However, edge solutions, such as our very own connected HBS hub solution, are resource-constrained in terms of compute, storage, and network. Therefore, we need to design the...
