This extension seamlessly integrates MQTT data with MySQL, unlocking the full potential of IoT data analytics.
Category: Data Integration
Version: Bundles with HiveMQ
License: Commercial
Provider: HiveMQ
Verified: Yes
MySQL is an open-source relational database management system widely used to store and manage structured data. The HiveMQ Enterprise Extension for MySQL makes it possible to:
Forward MQTT messages from IoT devices to one or more MySQL databases.
Convert MQTT messages into MySQL rows with convenient statement templates and insert statements.
Optimize data formatting for efficient data querying and quick analysis.
HiveMQ’s MQTT platform is the ideal choice for supplementing your investment in MySQL to unlock the full power of data analytics.
Analyze IoT data to provide real-time insights into device performance, user behavior, and environmental conditions for swift decision-making.
Utilize analytical tools with MySQL to query real-time sensor data and build predictive models for pattern identification and trend analysis.
Use MySQL to store and analyze new and historical IoT data to identify trends and patterns over time.
Create curated reports and dashboards, providing data visualization and empowering stakeholders to make informed decisions.
The MySQL Extension is compatible with other databases including:
HiveMQ extensions are plugins that provide seamless integration with streaming services, databases, data warehouses, and security services. There is a Custom SDK to build tailored extensions for specific integration needs.
Extensions usage scales along with the rest of the cluster and each enterprise extension is designed and tested for use in a cluster.
Extensions run on each cluster node, so if a node exits the cluster the extension will be present on the replacement node.
No separate nodes to manage. Easily manage cluster-wide configuration in a Kubernetes cluster with the HiveMQ Operator.
Choose between a fully-managed cloud or self-managed MQTT platform. Our MQTT experts can help you with your solution and demonstrate HiveMQ in action.