feeddriven

Feeddriven is a design principle in software engineering and information systems where system behavior is governed by continuous data feeds rather than static inputs. In a feeddriven architecture, components publish, subscribe to, and process streams of data events in real time, enabling incremental updates and responsive processing.

Key characteristics include event-driven messaging, asynchronous processing, loose coupling, and scalable backends. Systems typically rely on data feeds produced by sensors, applications, or external services, and distributed processing pipelines that apply transformations, enrichment, or aggregation as data flows. Common patterns include publish–subscribe, stream processing, and backpressure-aware consumers. Data consistency is often eventual, and components are designed to be idempotent and fault-tolerant.

Applications span content delivery, real-time dashboards, financial tick data, IoT platforms, social media aggregators, and continuous data integration. In practice, feeddriven architectures are supported by tools such as Apache Kafka or RabbitMQ for messaging, and frameworks like Apache Flink or Spark Streaming for processing. Storage layers may include immutable logs or object stores to facilitate replay and state management.

Advantages include real-time responsiveness, scalability, and decoupled components. Limitations involve added system complexity, the need for robust fault tolerance, and potential challenges with data quality and consistency.

See also: event-driven architecture, data streaming, publish–subscribe, reactive systems, streaming analytics.