A highly scalable and reliable MQTT broker platform for AI, IoT, IIoT, and connected vehicles, supporting multiple protocols and real-time data integration.
EMQX is an open-source, highly scalable MQTT broker platform designed for building real-time data infrastructure in IoT, AI, and connected vehicle applications. It connects millions of devices, processes messages with sub-millisecond latency, and integrates seamlessly with databases, cloud services, and message queues. The platform solves the challenge of reliable, secure, and high-performance communication in distributed systems.
IoT architects, backend engineers, and DevOps professionals building large-scale connected systems for industrial IoT, smart cities, connected vehicles, and AI-driven applications.
Developers choose EMQX for its massive scalability, comprehensive protocol support, and built-in data integration capabilities, which reduce the complexity of deploying and managing enterprise-grade MQTT infrastructure. Its unified feature set under the BSL license offers advanced functionality without vendor lock-in.
The most scalable and reliable MQTT broker for AI, IoT, IIoT and connected vehicles
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Capable of handling over 100 million concurrent MQTT clients with sub-millisecond latency, as stated in the scalability section, making it fit for massive IoT deployments.
Supports MQTT 5.0/3.x, MQTT over QUIC, and gateways for LwM2M, CoAP, and MQTT-SN, enabling connectivity across diverse IoT devices and use cases.
Features a SQL-based rule engine and seamless integration with 50+ backend systems like Kafka, PostgreSQL, and AWS Kinesis, allowing real-time data processing and routing.
Offers TLS/SSL, flexible authentication (JWT, certificates), and granular ACLs, providing robust security for sensitive IoT applications.
The shift to Business Source License 1.1 requires a license file for clustering from v5.9.0, adding administrative overhead and potential costs, as noted in the license section.
Rolling upgrades between certain versions are unsupported or have limitations, per the upgrade matrix, complicating maintenance and long-term version management.
Optimized for large-scale deployments, it can be over-engineered and resource-heavy for smaller projects, leading to higher operational complexity and costs.