The Apache StreamPipes community is pleased to announce release 0.91.0! Download the latest version .

Use Cases

Industrial IoT

Integrated adapters such as OPC UA and MQTT and data processors tailored at analyzing high-frequency sensor data make StreamPipes a great choice to quickly analyze machine data.
The ability to create geographically distributed pipelines make StreamPipes suitable for edge computing use cases.
Data sinks for popular databases such as Elasticsearch and the ability to integrate Machine Learning models into data processors enable use cases such aspredictive analytics and anomaly detection.


Incident Detection
StreamPipes allows to immediately detect incidents you'd like to avoid. We support algorithms ranging from simple threshold-based tracking of sensor measurements over trend analysis over time periods up to the integration of custom-tailored predictive maintenance algorithms.
Data Harmonization
StreamPipes helps to create a clean data lake based on sensor measurements from machines and other assets. Various data harmonization algorithms (e.g., filters, aggregations and unit converters) allow to easily clean and enrich data in a continuous fashion.
See what's happening right now: Use StreamPipes as your real-time window into your current production performance. A live dashboard and a wide range of available notification channels allow you to monitor KPI's in a flexible and customizable manner.