eKuiper—a lightweight IoT data analytics and streaming software—is now available in its 1.9.0 release. eKuiper, an LF Edge project, migrates real-time cloud streaming analytics frameworks such as Apache Spark, Apache Storm and Apache Flink to the edge. eKuiper references these cloud streaming frameworks, incorporates any special requirements of edge analytics and introduces rule engine, which is based on Source, SQL (business logic) and Sink; rule engine is used for developing streaming applications at the edge.
eKuiper 1.9 release continues to enhance the source/sink connectors to make it easier to connect and transmit data with lower bandwidth. The community has also enhanced the data transformation ability to flexibly encode and compress any part of your data. The 1.9 release adds a number of significant new features, among them are
- Multiple neuron connection to analyze collected data from multiple IOT gateways together
- MQTT sink/source compression/decompression support, save bandwidth for edge cloud communication
- HTTPPull source & REST sink support dynamic token based authentication, connect to more services out of box
- More transformation and compression functions added, handle your data flexibly
- Partial data export/import, migrate only interested rules and the dependencies
- Run python plugin in conda virtual environment, separate the python runtime env
Learn more about these and other features of eKuiper’s 1.9 release in the release notes.
In the next release, the community will adapt to the EdgeX Foundry‘s Minnesota version, while exploring the use of external states such as Redis states to achieve persistent states.