Seamless MQTT data integration into the Snowflake Data Cloud
Category: Data Integration
Version: Bundled with HiveMQ |
Provider: HiveMQ | Verified: yes
Product Resources Please use the following links to download and try the extension, read the installation guide, learn more about features, or find out how we can help.
About this Extension
The HiveMQ Enterprise Extension for Snowflake enables seamless MQTT data integration into the Snowflake Data Cloud via the Snowflake Snowpipe Streaming API. This purpose-built extension is part of the HiveMQ platform and eliminates the need for third-party MQTT data integration technologies. This extension was created using the Snowflake Ingestion SDK.
Why use Snowflake to integrate MQTT data from IoT Devices?
Snowflake’s Data Cloud platform provides the scalable architecture and ability to ingest diverse data sets needed to handle the processing and analyzing of IoT data. For instance, manufacturing companies use IoT sensor data and machine learning (in Snowflake) to predict equipment failures for proactive machine maintenance, reducing downtime and ensuring smooth operations.
This extension enables the following with Snowflake:
Ingest MQTT data in its original format into Snowflake
Ingest MQTT data in its original format into Snowflake, including payload, topic, timestamps, and more.
Use data transformation tools in Snowflake to create use-case-specific tables, ensuring flexibility for current and future applications.
Specify the MQTT topic data sent to Snowflake
Deliver MQTT messages from specific/relevant topics to Snowflake.
This helps optimize data storage and keep storage costs low.
Predictive Machine Maintenance using AI/ML capabilities
Apply machine learning algorithms to analyze historical data patterns from IoT sensors and predict equipment failures before they occur.
This helps keep machines running, reduces downtime, saves costs, and ensures smooth operations.
Smart Asset Tracking and Management
Sensors on trucks, containers, and other assets can continuously transmit location, temperature, and condition data.
Once ingested into Snowflake via the HiveMQ platform, this data can be used to:
Monitor asset locations in real-time,
Track temperature-sensitive cargo,
Determine the condition of high-value goods.
Use MQTT Data for Energy-efficient Smart Grids
Integrate MQTT data with Snowflake and use it to analyze historical energy consumption patterns and identify trends, enabling energy companies to implement energy-efficient strategies like:
This helps optimize energy usage, reduce costs, and promote sustainability
Download the latest version of the HiveMQ platform, which contains an evaluation version of this extension, limited to a 5-hour operating window. You can reset this window by restarting the HiveMQ broker each time. For the production version of this extension, please contact our sales team.