HiveMQ, a global leader in enterprise MQTT solutions, today announced the launch of the HiveMQ Enterprise Extension for Snowflake on the Snowflake AI Data Cloud. The integration enables organizations to seamlessly forward MQTT data into Snowflake, providing real-time insights, predictive analytics, and historical trend analysis.
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“HiveMQ’s mission is to make IoT data integration as seamless and efficient as possible, and the HiveMQ Enterprise Extension for Snowflake does exactly that,” said Dominik Obermaier, CEO and Co-Founder, HiveMQ. “By leveraging the Snowflake AI Data Cloud, we’re helping our joint customers unlock the full potential of their IoT data to drive smarter, data-driven decisions.”
HiveMQ is joining Snowflake in mobilizing the world’s data to help organizations simplify and scale IoT data integration. The HiveMQ Enterprise Extension for Snowflake uses Snowpipe Streaming API to ingest MQTT messages directly into Snowflake, including metadata such as payloads, topics, and timestamps. This allows organizations to analyze IoT data in real time, build predictive models, and visualize data trends, helping them optimize operations and reduce costs.
“HiveMQ’s commitment to collaborating with Snowflake can be seen through the launch of the HiveMQ Enterprise Extension for Snowflake,” said Pugal Janankiraman, Global Manufacturing CTO at Snowflake. “We look forward to driving deeper value for Snowflake’s AI Data Cloud ecosystem by working with HiveMQ to enable seamless IoT data integration and unlock actionable insights through Snowflake’s single, integrated platform.”
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HiveMQ’s collaboration with Snowflake enables joint customers to seamlessly combine IoT data with other business-critical datasets, reducing infrastructure complexity while improving scalability and reliability. This powerful integration ensures that customers can unlock the full value of IoT data across their operations, transforming how data is utilized in industrial and enterprise environments.
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