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. – Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): bit.ly/3KCnWXq