Tdengine already supports the industrial Intel edge insight package

To accelerate the digital transformation of traditional industries , Intel introduced industrial Intel Marginal insight （Intel Edge Insights for Industrial, hereinafter referred to as EII） software package . as everyone knows , In many aspects of industrial production , Will produce a large number of time series data （Time-Series Data）, Data is wealth , Through a comprehensive analysis of these data , It is possible to mine information that is very helpful for business decision-making , So as to further create value 、 Improve efficiency .

EII Can be in Docker Up operation , To separate infrastructure from applications , Enable users to develop faster .

Its official description is as follows ：

Industrial Intel The edge insight package is a pre validated 、 Ready to deploy software reference design , Specifically for video and time series data acquisition . It includes AI analysis , And can be published to local applications or remote . Because it's built on Docker On , Therefore, it is easy to modify , And it can be customized according to your application .

picture source ： Industrial Intel Edge insight package

（https://www.intel.cn/content/www/cn/zh/internet-of-things/industrial-iot/edge-insights-industrial.html）

Industrial Intel Edge insight packages are software stacks that have been validated in production environments , It can be safely extracted at the edge 、 Analyze and store video and timing data . As can be seen from the above architecture diagram , It is also very easy to write your own algorithm model on the software package .

TDengine It is open source developed by Taosi data 、 High performance 、 Distributed 、 Support SQL Time series database , In the Internet of things 、 Industrial Internet 、 Car networking 、IT Operation and maintenance 、 energy 、 Finance and so on .

• Through innovative storage engine design , Whether it's data writing or query ,TDengine The performance of is faster than that of general database 10 More than times , It is also far superior to other time series databases , And the storage space is greatly saved .

• Through native distributed design ,TDengine Provides the ability to scale horizontally , Only adding nodes can obtain stronger data processing capacity , At the same time, the high availability of the system is guaranteed through the multi copy mechanism .

• TDengine use SQL As a data query language , Reduce learning and migration costs , At the same time provide SQL Extended to handle time series data specific analysis , And support convenient and flexible schemaless Data writing .

Temporal data processing is EII Important modules in . To support the storage and analysis of time series data , at present EII The time series database used is InfluxDB. Follow InfluxDB comparison ,TDengine It has obvious advantages in performance and compression ratio . For specific comparison, please refer to relevant test reports ：《TDengine and InfluxDB Write the performance comparison test report 》 and 《TDengine and InfluxDB Query the performance comparison test report 》. therefore , Taosi data's engineers try to TDengine Introduced EII, The time series data can be saved in this more efficient time series database , Improve processing efficiency and reduce costs .（ The above comparison test report can be viewed on the document page of the official website after clicking to read the original ）

introduce TDengine after , The specific data flow is as follows ：

Interested readers can refer to it Intel Relevant documents on the website （https://www.intel.com/content/www/us/en/developer/articles/technical/tdengine-for-edge-insights-for-industrial.html  You need to copy the link to the browser to view ） To use EII + TDengine. Readers can refer to this document , Build your own Docker Mirror image . function EII after , have access to Telegraf To collect timing data , Keep it in TDengine In , And then you can use Grafana View... Graphically .

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