MQTT: Bridging IoT Data and #AI. The next AI leap comes from real-time IoT data. #MQTT is a great protocol to use when connecting device data with AI/ML services. Here’s how it enables smarter device data management:.🧵 1/

An MQTT bridge links different brokers to share messages—but without the right security, it becomes a risk. Security tips: .- TLS encryption.- Apply strict ACLs.- Strong auth (JWT, X.509).- Secure the broker's host with firewalls and updates. ➡️ More:

MQTT Security Tip: .Choose the right auth based on environment + device limits.- Username/pw: Easy, low-overhead, but weak if not over #TLS.- Token-based (e.g. JWT): Scalable + fine-grained, but complex.- TLS certs: Strongest, but hard to manage. ➡️ More:

Smart factories run on real-time data—but with diverse protocols like Modbus, OPC UA. Unifying that data is tough. MQTT solves this with a lightweight pub/sub model that decouples systems for scalable data flow. ➡️ Free white paper on MQTT in smart manu:

MQTT is widely used for IoT data. Amazon Kinesis handles large-scale, real-time processing on #AWS. With EMQX, you can:.- Ingest #MQTT data.- Filter/transform via Rule Engine.- Stream to Kinesis.- Analyze with Lambda/Flink/SageMaker. 🔗 More:

From MQTT to S3 Tables: You can now stream IoT data directly into Amazon S3 Tables (built on Apache #Iceberg). No complex ETL. No batch delays. Just real-time IoT data, ready for queries. AI-ready data stack. 📺👇 Demo below, watch the full demo in blog:

Why bridge MQTT & RocketMQ?. MQTT is great for IoT data; RocketMQ handles high-scale streaming. Together, they enable:.- Real-time telemetry: MQTT → RocketMQ for analytics.- Buffered processing for batch jobs.- Hybrid pub/sub + ordered messaging. ➡️More:

MQTT Security Tip: QoS levels impact both reliability and risk. QoS 0: Fast but no guarantee—use TLS + integrity checks.QoS 1: Watch for duplicates—use IDs + dedup logic.QoS 2: Most reliable, but resource-heavy—rate limit . ➡️ Get MQTT 101 ebook: .#MQTT

New integration in EMQX 5.10 with @doris_apache.

New feature in EMQX 5.10: .EMQX now supports native integration with Apache Doris, a fast MPP analytical database. #EMQX + #Doris Use cases: .- Monitor devices in real time.- Predictive maintenance.- Query across diverse data sources. ➡️ More:

MQTTX 1.12 is out 🚀 🚀 . Now with AI Copilot 2.0 (supporting Gemini, #Claude, GPT-4.1, #Azure), native MCP support, and exact-size payloads. Generate schemas, simulators, scripts using natural language with AI. ➡️ Learn more: . 👇 See demo below:

Running an MQTT broker on Docker offers many benefits: . - Portable: Deploy MQTT broker like #EMQX locally or in the cloud.- Isolated: No conflicts with other apps.- Scalable: Add more containers as needed.- Fast setup: Run in seconds. ➡️ Demo: .#MQTT

📢 Join our live webinar on July 8 to see demo of EMQX 5.10. See how to use GPT‑4, Claude & LLMs in MQTT data pipelines, stream IoT data to S3 with Apache Iceberg (no ETL!), and build real-time AI workflows. ⏰ 10am PT | 1pm ET | 6pm BST. 🔗 Register:

Smart vehicles need fast, reliable data flow, from telemetry to OTA updates. #EMQX supports MQTT over QUIC—built for mobile networks with low latency, encryption & seamless reconnection. 📥 Get free white paper, see how SAIC Volkswagen & Lotus use EMQX:

Simplify MQTT integration with EMQX Platform.- Works with Java, C#, Golang, Python.- Supports key MQTT client libraries.- Lets devs focus on app logic while it manages device messaging. ➡️ Try EMQX Platform for free:

Python + MQTT: Versatile Integration & Rapid Development. - Extensive libraries (Paho-MQTT) with minimal code.- Seamless integration with enterprise frameworks.- Rapid prototyping speeds time-to-market.- Ideal for system integration and backend APIs. 5/ .#python.

Golang + MQTT: High-Performance Distributed Systems.- Go's lightweight concurrency model handle thousands MQTT connections.- Memory-efficient with minimal runtime overhead.- Built-in cross-compilation for multiple architectures.- Good for microservices and real-time analytics. 4/.

C# + MQTT: Seamless .NET + Azure IoT integration. - Full Microsoft and Azure ecosystem support.- Libraries like M2Mqtt and MQTTnet makes implementation easy.- Works even on compact Windows IoT Core devices. 3/.

Java + MQTT: For enterprise-grade IoT systems. - Robust, scalable architecture.- Well-supported MQTT libraries.- Ideal for mission-critical systems that demand reliability.- Great fit for industrial automation, traffic systems, and smart homes. 2/ . #java.

Programming language to use with MQTT for enterprise & backend development:.Choosing the right language for MQTT matters, especially for enterprise IoT apps. Here’s how Java, C#, PHP, and Django stack up:.🧵 1/

MQTT Security Tip: Client ID Management. Every MQTT client must use a unique ID—but misuse can create risks. Best practices:.- Enforce unique IDs.- Reject empty IDs.- Validate format/length.- Bind IDs to auth. ➡️ Get free MQTT 101 book: #MQTT