Streaming IoT Data Between HiveMQ Cloud and Confluent Cloud
HiveMQ Cloud's Integration with Confluent Cloud
Confluent Cloud is a cloud-native and complete data streaming platform provided by Confluent, the company behind Apache Kafka®. Provided as a fully managed service, it enables businesses to harness the power of Kafka while bypassing the burdens of infrastructure management. Confluent Cloud offers a scalable and reliable messaging system for real-time data streaming and event-driven applications.
HiveMQ Cloud´s integration with Confluent Cloud enables bidirectional data transmission between IoT devices and Kafka clusters to seamlessly integrate MQTT data with Confluent Cloud.
Stream MQTT Data to Confluent Cloud via HiveMQ Cloud
The demo video shows how easy it is to start with the HiveMQ Cloud and Confluent Cloud to stream MQTT data in real-time.
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Here’s what the Confluent Cloud integration can do
Uni- and Bidirectional data transmission between IoT devices connected to HiveMQ and Kafka clusters on Confluent Cloud.
Supports all MQTT 3 and MQTT 5 features, including all QoS levels
Route MQTT messages to Kafka topics using wildcard MQTT topic filters.
Easily monitor bidirectional messages between HiveMQ and the Kafka cluster in HiveMQ Control Center.
Buffer messages on HiveMQ for high availability when Kafka is unavailable.
HiveMQ and Kafka Architecture
HiveMQ solves the issues of Kafka for IoT by seamlessly integrating MQTT messages into the Kafka messaging flow. Conversely, Kafka messages can be distributed to HiveMQ and MQTT clients. The HiveMQ broker is extended to include a native implementation of the Kafka protocol. This allows HiveMQ to transpose MQTT messages into the Kafka protocol and vice versa. Our architecture allows for full MQTT support of IoT data plus complete integration with Kafka.
Why Is HiveMQ & MQTT Needed for IoT Use Cases?
Kafka is well suited for sharing data between enterprise systems and applications located in a data center or in the cloud. However, for IoT use cases there are a number of reasons Kafka is not well suited:
Kafka brokers need to be addressed directly by the client which isn't the case for IoT devices that connect through load balancers.
Kafka clients require a stable IP connection which isn't always the case for IoT devices connecting over unreliable cellular networks.
Kafka does not support large amounts of topics so large IoT deployments with large topics spaces typically don't fit well into Kafka.
Kafka clients are complex and resource intensive so smaller constrained IoT devices often can't run a Kafka client.