eKuiper

eKuiper is an open-source edge stream processing engine (stream processing) for running lightweight analytics on Internet of Things (IoT) and other streaming data at resource-constrained edge environments.

• Rule-based stream processing for time-series and event data at the edge (stream processing)
• SQL-like rule engine for filtering, transformation, and aggregation of streams (data processing)
• Plugin model for sources, sinks, and functions to integrate with external systems (integration framework)
• Deployment on edge gateways, embedded Linux, and containerized environments (edge computing)
• Integration with LF Edge and IoT ecosystems for end-to-end edge-to-cloud data pipelines (IoT data infrastructure)

More About eKuiper

eKuiper is an open-source edge stream processing engine (stream processing) under the LF Edge umbrella that runs on resource-limited edge devices to execute real-time analytics on streaming data close to data sources such as sensors, industrial equipment, and gateways. It targets scenarios where bandwidth, latency, and privacy constraints make it practical to process data locally instead of forwarding all raw data to centralized cloud platforms.

The project provides a SQL-like rule engine (data processing) that allows users to define rules for filtering, transforming, and aggregating incoming data streams. These rules support operations such as projections, conditions, joins, and window-based aggregations on time or count windows, which are common patterns in time-series and event processing. The rule definitions are typically deployed to the eKuiper runtime, which then evaluates them continuously against inbound messages.

eKuiper implements a modular architecture with pluggable components (integration framework) for sources, sinks, and functions. Source plugins ingest data from message brokers and other streaming systems, while sink plugins deliver processed results to downstream systems or applications. Function plugins extend the processing engine with custom logic or domain-specific operators. This plugin framework allows adaptation of eKuiper to varied industrial, enterprise, and IoT environments without modifying the core engine.

The engine is designed for edge environments (edge computing), with a small runtime footprint that runs on embedded Linux devices, edge gateways, and container platforms. It can operate independently at the edge or as part of a broader edge-to-cloud architecture, where eKuiper handles local pre-processing and filtering before forwarding compacted insights to cloud services or data platforms.

In enterprise and institutional deployments, eKuiper supports use cases such as IoT telemetry filtering, device data normalization, event correlation, and real-time rule-based alerting (IoT data infrastructure). By executing logic where data is produced, organizations can reduce network utilization, improve local responsiveness, and maintain local control over which data leaves the site. Its alignment with LF Edge ties it into a wider ecosystem of open-source edge computing projects, enabling integration in standardized edge stacks.

From a taxonomy perspective, eKuiper falls into categories including edge stream processing, complex event processing, and IoT data pipeline orchestration (stream processing, IoT data infrastructure). It functions as a rules-driven processing layer between field data sources and upstream storage, analytics, or control systems, and its extensible plugin-based design provides a framework for connecting to diverse protocols, brokers, and enterprise backends.