Top 9 Architectural Patterns for Data and Communication Flow
Peer-to-Peer - The Peer-to-Peer pattern involves direct communication between two components without the need for a central coordinator.
API Gateway - An API Gateway acts as a single entry point for all client requests to the backend services of an application.
Pub-Sub - The Pub-Sub pattern decouples the producers of messages (publishers) from the consumers of messages (subscribers) through a message broker.
Request-Response - This is one of the most fundamental integration patterns, where a client sends a request to a server and waits for a response.
Event Sourcing - Event Sourcing involves storing the state changes of an application as a sequence of events.
ETL - ETL is a data integration pattern used to gather data from multiple sources, transform it into a structured format, and load it into a destination database.
Batching - Batching involves accumulating data over a period or until a certain threshold is met before processing it as a single group.
Streaming Processing - Streaming Processing allows for the continuous ingestion, processing, and analysis of data streams in real-time.
Orchestration - Orchestration involves a central coordinator (an orchestrator) managing the interactions between distributed components or services to achieve a workflow or business process.
