Seamless integration, dynamic schemas, and broad ecosystem support for your time-series data.
Ingest high-cardinality MQTT telemetry at scale with stable low latency
Keep hot and historical data in one place for fast unified queries
Reduce storage cost with compression and object storage integration
Query device metrics and events in SQL for dashboard and alert workflows
EMQX receives MQTT traffic from massive devices and forwards data through flexible pipelines, enabling reliable and scalable event flow.
GreptimeDB stores metrics and events with high compression and supports real-time and historical queries using a unified SQL interface.
Visualization and monitoring tools connect through standard protocols to build dashboards, alerts, and automated operations around live device data.
Proven scenarios where GreptimeDB and EMQX deliver measurable results.
Collect GPS, CAN bus, and sensor data from millions of vehicles via MQTT. Real-time fleet monitoring with SQL dashboards and long-term analysis for predictive maintenance.
Ingest PLC and sensor readings at high frequency for equipment health tracking. Anomaly detection on vibration, temperature, and pressure with a unified view across production lines.
Aggregate meter readings from distributed energy assets in real time. Track generation, consumption, and grid metrics with cost-effective long-term storage for compliance and optimization.
Monitor HVAC, access control, and environmental sensors across sites. Track assets via BLE/LoRa/MQTT gateways with centralized observability for facility and logistics operations.
It is a purpose-built integration that connects GreptimeDB's time-series database directly with EMQX's MQTT broker. Together, they provide a seamless pipeline from device data ingestion to storage, querying, and analytics — without requiring a separate ETL pipeline or middleware.
GreptimeDB provides a native data sink for EMQX. You configure the GreptimeDB connector in EMQX's Rule Engine or data bridge, select the MQTT topics to persist, and data starts flowing automatically. It also supports schema-on-the-fly, which infers the data structure from your JSON payloads without any upfront DDL.
No. GreptimeDB supports schema-on-the-fly — it automatically discovers and creates tables and columns based on incoming MQTT message payloads. You can start ingesting data immediately.
GreptimeDB supports SQL for complex queries and analysis, PromQL for Prometheus-compatible metric queries, and InfluxDB Line Protocol for ingestion. It also provides PostgreSQL and MySQL wire protocol compatibility, making it easy to integrate with existing tools like Grafana, Metabase, and DBeaver.
GreptimeDB is purpose-built for high-cardinality time-series workloads. Its native multi-value data model and columnar storage engine efficiently handle millions of unique time series from devices, sensors, and vehicles — without the cardinality explosion problems common in traditional TSDBs.
GreptimeDB integrates out-of-the-box with popular visualization and BI tools including Grafana, Metabase, and Streamlit. You can build real-time dashboards and monitoring views with just a few clicks using SQL or PromQL queries.
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