IoT scenarios often face challenges like a large number of devices, high data generation rates, and huge accumulated data volumes. Therefore, how to access, store, and process these massive amounts of data has become a critical issue.
EMQX, as a highly scalable, powerful, and feature-rich MQTT broker for the IoT, can handle billions of concurrent connections and millions of messages per second in a single cluster. Furthermore, its built-in Enterprise Data Integration functionality provides an out-of-the-box solution that seamlessly integrates IoT data with more than 40 types of data systems, including cloud services and on-premised systems, say Kafka, SQL, NoSQL, and time-series databases.
In order to provide users with a comprehensive understanding of the "out-of-the-box" usability and powerful performance of EMQX Enterprise data integrations, we conducted benchmark tests on integrating single-node EMQX Enterprise with databases, messaging platforms and cloud services, and compiled a series of test reports. Through these reports, users can learn about the characteristics of various databases or messaging queues, how to configure and use the integrations, as well as the performance metrics. We believe that this information can help IoT users choose the most suitable EMQX integration solution for their business.
In this report, we will first introduce how to use the PostgreSQL data bridge, covering topics like how to set up the PostgreSQL server and create data bridges and rules for forwarding data to it. Then, we will elaborate on the process and results of the tests, with an analysis of related metrics.