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Architecture Data Flow

Top 9 Architectural Patterns for Data and Communication Flow

Explore 9 key architectural patterns for efficient data and communication.

  • 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.