How does EMQX ensure zero data loss for mission-critical IoT applications?
EMQX achieves zero data loss through its durable message queue and built-in distributed and replicated storage layer, powered by RocksDB and Raft consensus. This ensures messages persist even if subscribers are offline, with configurable TTL, dispatch strategies, and last-value semantics.
Can EMQX integrate with specific AI models like Google Gemini for real-time data processing?
Yes, EMQX offers native integration with leading AI models, including OpenAI GPT, Anthropic Claude, and Google Gemini. This allows for real-time processing of MQTT payloads, enabling features like anomaly detection and intelligent alert generation directly from IoT data streams.
What is the primary difference between the BYOC and Enterprise plans for self-managed deployments?
In the BYOC (Bring Your Own Cloud) plan, EMQX manages monitoring and maintenance, providing assistance with issue resolution. Conversely, the self-managed Enterprise plan requires customers to handle their own monitoring and maintenance responsibilities.
How does EMQX's rule engine facilitate on-the-fly data transformation for IoT data?
The built-in SQL-based rule engine in EMQX allows users to extract, filter, enrich, and transform IoT data in real-time. This is further enhanced by a schema registry, message codec, and a visual flow editor, providing powerful capabilities for data manipulation before integration with other systems.
What protocols does EMQX support beyond MQTT for device connectivity?
Beyond MQTT, EMQX supports various open standard protocols for device connectivity, including HTTP, QUIC, and LwM2M/CoAP, providing flexibility for integrating diverse IoT devices and systems.