berichtenqueues

Berichtenqueues, often referred to in English-language documentation as message queues, describe a pattern for asynchronous communication between software components. A queue provides a temporary storage area where producers can place messages and consumers can retrieve them later. By decoupling sender and receiver in time and rate, berichtenqueues help absorb bursts of work, improve resilience, and enable scalable, fault-tolerant architectures.

Core elements include producers that generate messages, a queue or broker that stores them, and consumers that process messages. Messages can be persisted to durable storage to survive restarts. Many implementations support delivery guarantees (at least once, at most once, or exactly once), acknowledgment workflows, and features such as message retries and dead-letter queues for failed processing.

Common queue patterns are point-to-point (one producer, one consumer per message) and publish-subscribe (where multiple consumers can receive copies of the same message). Some systems expose queues, topics, or exchanges with routing rules to control how messages are delivered. Prominent software in this space includes RabbitMQ, Apache ActiveMQ, Amazon SQS, Azure Service Bus, and Google Cloud Pub/Sub; Kafka is related but centered on a distributed log rather than traditional queues.

Berichtenqueues are widely used for background task processing, event-driven workflows, order processing, email sending, and other asynchronous workloads in microservice architectures. When evaluating an implementation, considerations include throughput, latency, durability, ordering guarantees, scalability, partitioning, schema evolution, and idempotency requirements. Security, monitoring, and operation simplicity are also important.

Although often grouped with event streaming, berichtenqueues emphasize decoupled, asynchronous task handling with bounded capacity and controlled retry semantics. They remain a foundational pattern for resilient, scalable systems.