DataStreamingSimulatoren

DataStreamingSimulatoren is a software framework used to generate synthetic data streams for testing, benchmarking, and developing streaming data pipelines. It focuses on providing controllable, repeatable workloads that mimic characteristics of real-time data without requiring live production data. The tool can produce continuous or bursty streams with configurable inter-arrival times, event timestamps, and data quality characteristics, enabling evaluation of latency, throughput, backpressure, and windowing behavior in stream processing systems.

It supports multiple data schemas and encodings, such as JSON and Avro, and can emit to common sinks or transports, including message queues, files, or stream platforms. The simulator offers domain templates for sensors, clickstreams, logs, or financial ticks, and allows custom scenario definitions to model correlations across streams, time-based patterns, and fault conditions. Features often include time progression control, watermark generation, out-of-order delivery, simulated delays, data gaps, and error injection. It can replay historical traces or generate synthetic data in real time, and export telemetry for monitoring and benchmarking.

Architecture typically comprises a core data generator, a scenario manager, sink adapters, and a telemetry layer, with a programmable interface such as JSON or YAML or a small domain-specific language. Usage scenarios include testing and benchmarking Apache Flink, Spark Structured Streaming, Kafka Streams, or other streaming engines, validating backpressure behavior, capacity planning, and reliability under adverse conditions.