MQTT Data Integration with PostgreSQL

MQTT Data Integration with PostgreSQL

author Nasir Qureshi

Written by Nasir Qureshi

Category: PostgreSQL MQTT Smart Manufacturing IIoT

Published: July 13, 2023

We are pleased to introduce our latest data integration extension for PostgreSQL, one of the most popular and advanced open-source databases for enterprise-grade data storage, processing, and analysis. It is part of our rapidly growing suite of data integration solutions for data analytics and streaming platforms.

Additionally, the PostgreSQL extension can be used to integrate MQTT data with:

  1. Timescale: The leading open-source time-series database for scalable and performant time-series data management and analytics.
  2. CockroachDB: A globally distributed SQL database for resilient, scalable, and low-latency data operations across multiple regions.

Try the HiveMQ platform now with the Enterprise Extension for PostgreSQL for free.

About the Enterprise Extension for PostgreSQL

The HiveMQ Enterprise Extension for PostgreSQL allows seamless integration with PostgreSQL, enabling organizations to store, process, and analyze IoT data within a robust and reliable relational database. Through efficient data ingestion and flexible data modelling, it empowers users to harness powerful SQL capabilities for real-time analytics. This unlocks the full potential of IoT data, enabling informed decision-making and actionable insights.

The extension secures MQTT data with robust TLS encryption and features a unique, fully customizable templating system that allows users to define the precise data format in PostgreSQL. This ensures MQTT messages can be formatted optimally for streamlined data querying.

TLS encryption:

This extension can be configured to enable TLS encryption between HiveMQ and PostgreSQL. You must configure PostgreSQL and the driver separately. Details on configuring TLS encryption with PostgreSQL can be found in the extension’s documentation.

Fully customizable templating system:

This extension’s fully customizable templating system helps you define your documents’ exact format. This ensures the data is ingested and stored in PostgreSQL according to your operational requirements. It also helps optimize data formatting for efficient data querying and quick analysis.

HiveMQ and PostgreSQL Enable Real-Time Monitoring, Advanced Analytics, and Predictive Maintenance in Smart Manufacturing

Manufacturing businesses are increasingly adopting smart manufacturing technologies to optimize their operations. According to a recent report by Rockwell Automation, smart manufacturing adoption grew by 50% year over year (2021-2022).

IoT sensors generate real-time data, providing manufacturers with immediate insights into production processes, machine performance, and quality control. This empowers proactive decision-making, optimized resource allocation, and predictive maintenance. Real-time monitoring of key performance indicators can enhance operational efficiency, minimize downtime, elevate product quality, and deliver exceptional customer experiences.

HiveMQ’s MQTT Broker Ingests Data from Smart Sensors

The HiveMQ MQTT broker captures real-time data from IoT sensors embedded in manufacturing equipment, such as temperature, pressure, and machine status. It transmits this data securely and reliably to the PostgreSQL database via its proprietary extension.

The Enterprise Extension for PostgreSQL Seamlessly Integrates MQTT Data With the PostgreSQL Database

The HiveMQ PostgreSQL Extension facilitates seamless integration between the MQTT broker and the chosen database, allowing MQTT data to be directly ingested and stored.

If you’re dealing with time-series data, Timescale is an ideal solution. It’s great at handling high-frequency data, which means you can store, compress, and retrieve manufacturing sensor data with ease. Plus, if you need to integrate MQTT data, the HiveMQ Enterprise Extension for PostgreSQL can seamlessly integrate MQTT data with Timescale as well.

Query Data from PostgreSQL in Real-time for Monitoring and Analytics

PostgreSQL can help manufacturers with real-time monitoring, analytics, and predictive maintenance. It enables SQL querying and live visualizations to detect patterns and anomalies in sensor data, optimizing the manufacturing process and increasing productivity.

Get Started With the Enterprise PostgreSQL Extension

If you haven’t already, download the latest free trial version of the HiveMQ platform. After that, follow the instructions from our PostgreSQL documentation to get started.

Contact Us to Explore How HiveMQ can Help

Learn more about using HiveMQ’s full-featured MQTT platform to publish MQTT data to PostgreSQL for persistent storage. Reach out to us to learn how we can help!

author Nasir Qureshi

About Nasir Qureshi

Nasir Qureshi is a Senior Product Marketing Manager at HiveMQ. With a passion for working on disruptive technology products, Nasir has helped SaaS companies in their hyper-growth journey for over 3 years now. He holds an MBA from California State University with a major in Technology and Data Management. His interests include IoT devices, networking, data security, and privacy.

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