Third Party Tools

Since TDengine supports standard SQL commands, common database connector standards (e.g., JDBC), ORM, and other popular time-series database writing protocols (e.g., InfluxDB Line Protocol, OpenTSDB JSON, OpenTSDB Telnet, etc.), it is very easy to integrate TDengine with other third party tools. You only need to provide simple configuration, the integration can be done without a line of code.

📄️ Grafana

TDengine can be quickly integrated with the open-source data visualization system Grafana to build a data monitoring and alerting system. The whole process does not require any code development. And you can visualize the contents of the data tables in TDengine on a dashboard.

📄️ Prometheus

Prometheus is a widespread open-source monitoring and alerting system. Prometheus joined the Cloud Native Computing Foundation (CNCF) in 2016 as the second incubated project after Kubernetes, which has a very active developer and user community.

📄️ Telegraf

Telegraf is a viral, open-source, metrics collection software. Telegraf can collect the operation information of various components without having to write any scripts to collect regularly, reducing the difficulty of data acquisition.

📄️ collectd

collectd is a daemon used to collect system performance metric data. collectd provides various storage mechanisms to store different values. It periodically counts system performance statistics while the system is running and storing information. You can use this information to help identify current system performance bottlenecks and predict future system load.

📄️ StatsD

StatsD is a simple daemon for aggregating application metrics, which has evolved rapidly in recent years into a unified protocol for collecting application performance metrics.

📄️ icinga2

icinga2 is an open-source, host and network monitoring software initially developed from the Nagios network monitoring application. Currently, icinga2 is distributed under the GNU GPL v2 license.

📄️ TCollector

TCollector is part of openTSDB and collects client computer's logs to send to the database.

📄️ EMQX Broker

MQTT is a popular IoT data transfer protocol. EMQX is an open-source MQTT Broker software. You can write MQTT data directly to TDengine without any code. You only need to setup "rules" in EMQX Dashboard to create a simple configuration. EMQX supports saving data to TDengine by sending data to a web service and provides a native TDengine driver for direct saving in the Enterprise Edition. Please refer to the EMQX official documentation for details on how to use it.).

📄️ HiveMQ Broker

HiveMQ is an MQTT broker that provides community and enterprise editions. HiveMQ is mainly for enterprise emerging machine-to-machine M2M communication and internal transport, meeting scalability, ease of management, and security features. HiveMQ provides an open-source plug-in development kit. MQTT data can be saved to TDengine via TDengine extension for HiveMQ. Please refer to the HiveMQ extension - TDengine documentation for details on how to use it.

📄️ Kafka

TDengine Kafka Connector contains two plugins: TDengine Source Connector and TDengine Sink Connector. Users only need to provide a simple configuration file to synchronize the data of the specified topic in Kafka (batch or real-time) to TDengine or synchronize the data (batch or real-time) of the specified database in TDengine to Kafka.

📄️ JupyterLab

JupyterLab is the next generation of the ubiquitous Jupyter Notebook. In this note we show you how to install the TDengine Python connector to connect to TDengine in JupyterLab. You can then insert data and perform queries against the TDengine instance within JupyterLab.