@@ -20,28 +20,30 @@ English | [简体中文](README-CN.md) | We are hiring, check [here](https://tde
# What is TDengine？
TDengine is an open source, cloud native time-series database optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. It enables efficient, real-time data ingestion, processing, and monitoring of TB and even PB scale data per day, generated by billions of sensors and data collectors. TDengine differentiates itself from other TSDBs with the following advantages.:
TDengine is an open source, high performance, cloud native time-series database optimized for Internet of Things (IoT), Connected Cars, and Industrial IoT. It enables efficient, real-time data ingestion, processing, and monitoring of TB and even PB scale data per day, generated by billions of sensors and data collectors. TDengine differentiates itself from other TSDBs with the following advantages.:
- High-Performance: TDengine is the only time-series database to solve the high cardinality issue to support billions of data collection points while out performing other time-series databases for data ingestion, querying and data compression.
- Simplified Solution: Through built-in caching, stream processing and data subscription features, TDengine provides a simplified solution for time-series data processing. It reduces system design complexity and operation costs significantly.
- Cloud Native: Through native distributed design, sharding and partitioning, separation of compute and storage, RAFT, support for kubernetes deployment and full observability, TDengine can be deployed on public, private or hybrid clouds.
- Open Source: TDengine’s core modules, including cluster feature, are all available under open source licenses. It has gathered 18.8k stars on GitHub, an active developer community, and over 137k running instances worldwide.
- Cloud Native: Through native distributed design, sharding and partitioning, separation of compute and storage, RAFT, support for kubernetes deployment and full observability, TDengine is a cloud native Time-Series Database and can be deployed on public, private or hybrid clouds.
- Ease of Use: For administrators, TDengine significantly reduces the effort to deploy and maintain. For developers, it provides a simple interface, simplified solution and seamless integrations for third party tools. For data users, it gives easy data access.
- Easy Data Analytics: Through super tables, storage and compute separation, data partitioning by time interval, pre-computation and other means, TDengine makes it easy to explore, format, and get access to data in a highly efficient way.
- Open Source: TDengine’s core modules, including cluster feature, are all available under open source licenses. It has gathered 18.8k stars on GitHub, an active developer community, and over 137k running instances worldwide.
# Documentation
For user manual, system design and architecture, please refer to [TDengine Documentation](https://docs.tdengine.com)(中文版请点击[这里](https://docs.taosdata.com))
For user manual, system design and architecture, please refer to [TDengine Documentation](https://docs.tdengine.com)([中文版](https://docs.taosdata.com))
# Building
At the moment, TDengine server supports running on Linux and Windows systems. You can choose to [install from packages](https://www.taosdata.com/en/getting-started/#Install-from-Package) or build it from the source code. This quick guide is for installation from the source only.
We provide a few useful tools such as taosBenchmark (was named taosdemo) and taosdump. They were part of TDengine. By default, TDengine compiling does not include taosTools. You can use 'cmake .. -DBUILD_TOOLS=true' to make them be compiled with TDengine.
To build TDengine, use [CMake](https://cmake.org/) 3.0.2 or higher versions in the project directory.
We provide a few useful tools such as taosBenchmark (was named taosdemo) and taosdump. They were part of TDengine. From TDengine 2.4.0.0, taosBenchmark and taosdump were not released together with TDengine.
By default, TDengine compiling does not include taosTools. You can use 'cmake .. -DBUILD_TOOLS=true' to make them be compiled with TDengine.
To build the [taosTools](https://github.com/taosdata/taos-tools) on Ubuntu/Debian, the following packages need to be installed.
```bash
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### Setup golang environment
TDengine includes a few components developed by Go language. Please refer to golang.org official documentation for golang environment setup.
TDengine includes a few components like taosAdapter developed by Go language. Please refer to golang.org official documentation for golang environment setup.
Please use version 1.14+. For the user in China, we recommend using a proxy to accelerate package downloading.
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@@ -101,7 +100,7 @@ go env -w GOPROXY=https://goproxy.cn,direct
### Setup rust environment
TDengine includees a few compoments developed by Rust language. Please refer to rust-lang.org official documentation for rust environment setup.
TDengine includes a few compoments developed by Rust language. Please refer to rust-lang.org official documentation for rust environment setup.
## Get the source codes
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@@ -140,14 +139,7 @@ cmake .. -DBUILD_TOOLS=true
make
```
Note TDengine 2.3.x.0 and later use a component named 'taosAdapter' to play http daemon role by default instead of the http daemon embedded in the early version of TDengine. The taosAdapter is programmed by go language. If you pull TDengine source code to the latest from an existing codebase, please execute 'git submodule update --init --recursive' to pull taosAdapter source code. Please install go language version 1.14 or above for compiling taosAdapter. If you meet difficulties regarding 'go mod', especially you are from China, you can use a proxy to solve the problem.
```
go env -w GO111MODULE=on
go env -w GOPROXY=https://goproxy.cn,direct
```
The embedded http daemon still be built from TDengine source code by default. Or you can use the following command to choose to build taosAdapter.
Note TDengine 2.3.x.0 and later use a component named 'taosAdapter' to play http daemon role. If you pull TDengine source code to the latest from an existing codebase, please execute 'git submodule update --init --recursive' to pull taosAdapter source code, and use the following command to choose to build taosAdapter.
If you use the Visual Studio 2013, please open a command window by executing "cmd.exe".
Please specify "amd64" for 64 bits Windows or specify "x86" is for 32 bits Windows when you execute vcvarsall.bat.
Please specify "amd64" for 64 bits Windows or specify "x86" for 32 bits Windows when you execute vcvarsall.bat.
```cmd
mkdir debug && cd debug
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@@ -184,7 +176,7 @@ nmake
If you use the Visual Studio 2019 or 2017:
please open a command window by executing "cmd.exe".
Please specify "x64" for 64 bits Windows or specify "x86" is for 32 bits Windows when you execute vcvarsall.bat.
Please specify "x64" for 64 bits Windows or specify "x86" for 32 bits Windows when you execute vcvarsall.bat.
```cmd
mkdir debug && cd debug
...
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@@ -237,19 +229,6 @@ taos
If TDengine shell connects the server successfully, welcome messages and version info are printed. Otherwise, an error message is shown.
### Install TDengine by apt-get
If you use Debian or Ubuntu system, you can use 'apt-get' command to install TDengine from official repository. Please use following commands to setup:
根据元数据信息中的 End Point 信息，将查询请求序列化后发送到该表所在的数据节点（dnode）。dnode 接收到查询请求后，识别出该查询请求指向的虚拟节点（vnode），将消息转发到 vnode 的查询执行队列。vnode 的查询执行线程建立基础的查询执行环境，并立即返回该查询请求，同时开始执行该查询。
