HiveMQ, an enterprise MQTT solutions provider, announced general availability of the HiveMQ Enterprise Data Lake Extension to enable MQTT data lake integration. Building data models for machine learning, AI, and other advanced analytics initiatives requires large volumes of IoT data. The HiveMQ Enterprise Data Lake Extension helps companies move that data with seamless integration to data lakes on Amazon, Google, Azure, Databricks, and other providers. Integrating IoT data into the data warehouse empowers businesses to extract valuable insights for analytics, data engineering, and machine learning, driving impactful AI use cases.
The new HiveMQ Enterprise Data Lake Extension helps:
Integrate IoT data via MQTT to cloud storage seamlessly, efficiently, and at scale.
Optimize storage costs by only ingesting the MQTT topics needed into cloud storage.
HiveMQ is purpose-built to connect anything via MQTT, communicate reliably, and control IoT data. The platform can be deployed anywhere, on-premise, or in the cloud, giving users the flexibility and freedom they need to evolve as their IoT deployment grows. The extensible platform provides seamless connectivity to the leading data streaming, databases, and data analytics platforms, plus offers a custom SDK for use with any stack.