The data model employed by TDengine is similar to that of a relational database. You have to create databases and tables. You must design the data model based on your own business and application requirements. You should design the STable (an abbreviation for super table) schema to fit your data. This chapter will explain the big picture without getting into syntactical details.
description:Briefly introduce how to replicate data among TDengine cloud services
description:Replicate data between TDengine cloud services
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TDengine provides full support for data replication. You can replicate data from TDengine cloud service to local TDengine, from local TDengine to TDengine cloud service, or from one cloud service to another one and it doesn't matter which cloud or region the two services reside in.
description:This topic introduces how to write data into TDengine from Prometheus.
description:Write data into TDengine from Prometheus.
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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.
description:This section explains how to write data into TDengine from telegraf.
description:Write data into TDengine from telegraf.
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Telegraf is an 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.
Raw time-series data is often cleaned and preprocessed before being permanently stored in a database. Stream processing components like Kafka, Flink, and Spark are often deployed alongside a time-series database to handle these operations, increasing system complexity and maintenance costs.