Cluster Support in Community Edition (CE)

Hi @iviliev ,

Great to see your interest in MQTT and HiveMQ, welcome to the community!

It’s possible to implement your own cluster service in HiveMQ CE using the HiveMQ CE extension SDK, but it may not provide full horizontal scalability and high availability (HA) capabilities. Implementing a cluster service on your own can be complex and may require a significant amount of effort, including testing and maintenance.

Additionally, the HiveMQ CE extension SDK does not provide built-in features for data replication and automatic failover, which are critical for achieving horizontal scalability and high availability. Therefore, if you implement your own cluster service using the HiveMQ CE extension SDK, you would need to build these features yourself, which can be a challenging and time-consuming task.

HiveMQ Enterprise Edition (EE) includes features to provide high availability (HA) and horizontal scalability. Some of the key features for data replication in HiveMQ Enterprise Edition include:

  1. Automatic Failover: HiveMQ EE supports automatic failover between broker nodes in a cluster, ensuring that there is no downtime in case of a failure.
  2. Data Replication: HiveMQ EE supports real-time data replication between nodes in a cluster, ensuring that data is consistently available on all nodes.
  3. Load Balancing: HiveMQ EE provides load balancing capabilities to distribute client connections evenly across all nodes in a cluster, improving scalability and performance.
  4. Cluster Management: HiveMQ EE provides a unified management interface for managing and monitoring the entire cluster, making it easy to manage and monitor large-scale deployments.

These features, along with others, help ensure high availability, horizontal scalability, and consistent data access for applications using HiveMQ Enterprise Edition.

If you need horizontal scalability and high availability, it may be more effective to consider using HiveMQ Enterprise Edition (EE).

I hope this helps.

Kind regards,
Dasha from HiveMQ Team