A distributed MQTT broker built on Kafka, handling 100M+ connections and 10M+ messages/sec with industrial-grade persistence.
TBMQ is a scalable, fault-tolerant, and durable MQTT broker designed for massive IoT deployments. It provides industrial-grade persistence by leveraging Apache Kafka, ensuring no data loss while supporting millions of concurrent connections and high message throughput. The broker is fully compliant with MQTT v3.1, v3.1.1, and v5.0 protocols for seamless interoperability.
IoT platform architects and developers building large-scale, mission-critical IoT systems that require handling millions of concurrent device connections and high message volumes with guaranteed delivery. It is also suited for organizations needing a masterless, horizontally scalable MQTT broker with enterprise security and monitoring features.
Developers choose TBMQ for its unique combination of massive scalability (over 100 million connections per cluster), Kafka-backed durability eliminating message loss, and masterless fault-tolerant architecture. It excels in demanding IoT messaging scenarios like fan-in, fan-out, and point-to-point communication with single-digit latency and comprehensive real-time monitoring.
The ultimate distributed MQTT broker. Handles 100M+ connections and 10M msg/sec with ease. Built on Kafka to provide industrial-grade persistence and eliminate data loss.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Horizontally scales to manage over 100 million MQTT connections on a single cluster, as validated in performance tests, making it ideal for large IoT deployments.
Leverages Apache Kafka for guaranteed message persistence and replication, ensuring no data loss in critical IoT applications, as highlighted in the architecture.
Provides multiple authentication methods (Basic, JWT, X.509, SCRAM) and per-client ACLs, offering robust security for industrial IoT, as documented in the security guides.
Includes dashboards for tracking sessions, subscriptions, and throughput in real time, enhancing operational visibility, as shown in the UI screenshots.
Requires Apache Kafka and cluster setup, increasing deployment and maintenance overhead compared to simpler, standalone MQTT brokers.
The integration with Kafka and advanced features necessitate expertise in both MQTT and distributed systems, which can be challenging for teams new to such architectures.
Designed for massive throughput, it may consume unnecessary resources for low-volume use cases, where lighter alternatives are more cost-effective and easier to manage.