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Table of Contents

1. Introduction
2. Documentation
3. Prerequisites
   • 3.1 Prerequisites On Linux
   • 3.2 Prerequisites On macOS
   • 3.3 Prerequisites On Windows
   • 3.4 Clone the repo
4. Building
   • 4.1 Build on Linux
   • 4.2 Build on macOS
   • 4.3 Build On Windows
5. Packaging
6. Installation
   • 6.1 Install on Linux
   • 6.2 Install on macOS
   • 6.3 Install on Windows
7. Running
   • 7.1 Run TDengine on Linux
   • 7.2 Run TDengine on macOS
   • 7.3 Run TDengine on Windows
8. Testing
9. Releasing
10. Workflow
11. Coverage
12. Contributing

1. Introduction

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 time-series databases 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 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 19.9k stars on GitHub. There is an active developer community, and over 139k running instances worldwide.

For a full list of TDengine competitive advantages, please check here. The easiest way to experience TDengine is through TDengine Cloud.

2. Documentation

For user manual, system design and architecture, please refer to TDengine Documentation (TDengine 文档)

3. Prerequisites

3.1 On Linux

Install required tools on Linux

For Ubuntu 18.04、20.04、22.04

sudo apt-get udpate
sudo apt-get install -y gcc cmake build-essential git libjansson-dev \
  libsnappy-dev liblzma-dev zlib1g-dev pkg-config

For CentOS 8

sudo yum update
yum install -y epel-release gcc gcc-c++ make cmake git perl dnf-plugins-core 
yum config-manager --set-enabled powertools
yum install -y zlib-static xz-devel snappy-devel jansson-devel pkgconfig libatomic-static libstdc++-static 

3.2 On macOS

Install required tools on macOS

Please intall the dependencies with brew.

brew install argp-standalone gflags pkgconfig

3.3 On Windows

Install required tools on Windows

Work in Progress.

3.4 Clone the repo

Clone the repo

Clone the repository to the target machine:

git clone /~https://github.com/taosdata/TDengine.git
cd TDengine

NOTE: TDengine Connectors can be found in following repositories: JDBC Connector, Go Connector, Python Connector, Node.js Connector, C# Connector, Rust Connector.

4. Building

At the moment, TDengine server supports running on Linux/Windows/MacOS systems. Any application can also choose the RESTful interface provided by taosAdapter to connect the taosd service. TDengine supports X64/ARM64 CPU, and it will support MIPS64, Alpha64, ARM32, RISC-V and other CPU architectures in the future. Right now we don't support build with cross-compiling environment.

You can choose to install through source code, container, installation package or Kubernetes. This quick guide only applies to install from source.

TDengine 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 3.13.0 or higher versions in the project directory.

4.1 Build on Linux

Detailed steps to build on Linux

You can run the bash script build.sh to build both TDengine and taosTools including taosBenchmark and taosdump as below:

./build.sh

It equals to execute following commands:

mkdir debug && cd debug
cmake .. -DBUILD_TOOLS=true -DBUILD_CONTRIB=true
make

You can use Jemalloc as memory allocator instead of glibc:

cmake .. -DJEMALLOC_ENABLED=true

TDengine build script can auto-detect the host machine's architecture on x86, x86-64, arm64 platform. You can also specify architecture manually by CPUTYPE option:

cmake .. -DCPUTYPE=aarch64 && cmake --build .

4.2 Build on macOS

Detailed steps to build on macOS

Please install XCode command line tools and cmake. Verified with XCode 11.4+ on Catalina and Big Sur.

mkdir debug && cd debug
cmake .. && cmake --build .

4.3 Build on Windows

Detailed steps to build on Windows

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" for 32 bits Windows when you execute vcvarsall.bat.

mkdir debug && cd debug
"C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\vcvarsall.bat" < amd64 | x86 >
cmake .. -G "NMake Makefiles"
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" for 32 bits Windows when you execute vcvarsall.bat.

mkdir debug && cd debug
"c:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Auxiliary\Build\vcvarsall.bat" < x64 | x86 >
cmake .. -G "NMake Makefiles"
nmake

Or, you can simply open a command window by clicking Windows Start -> "Visual Studio < 2019 | 2017 >" folder -> "x64 Native Tools Command Prompt for VS < 2019 | 2017 >" or "x86 Native Tools Command Prompt for VS < 2019 | 2017 >" depends what architecture your Windows is, then execute commands as follows:

mkdir debug && cd debug
cmake .. -G "NMake Makefiles"
nmake

5. Packaging

The TDengine community installer can NOT be created by this repository only, due to some component dependencies. We are still working on this improvement.

6. Installation

6.1 Install on Linux

Detailed steps to install on Linux

After building successfully, TDengine can be installed by:

sudo make install

Installing from source code will also configure service management for TDengine. Users can also choose to install from packages for it.

6.2 Install on macOS

Detailed steps to install on macOS

After building successfully, TDengine can be installed by:

sudo make install

6.3 Install on Windows

Detailed steps to install on windows

After building successfully, TDengine can be installed by:

nmake install

7. Running

7.1 Run TDengine on Linux

Detailed steps to run on Linux

To start the service after installation on linux, in a terminal, use:

sudo systemctl start taosd

Then users can use the TDengine CLI to connect the TDengine server. In a terminal, use:

taos

If TDengine CLI connects the server successfully, welcome messages and version info are printed. Otherwise, an error message is shown.

If you don't want to run TDengine as a service, you can run it in current shell. For example, to quickly start a TDengine server after building, run the command below in terminal: (We take Linux as an example, command on Windows will be taosd.exe)

./build/bin/taosd -c test/cfg

In another terminal, use the TDengine CLI to connect the server:

./build/bin/taos -c test/cfg

Option -c test/cfg specifies the system configuration file directory.

7.2 Run TDengine on macOS

Detailed steps to run on macOS

To start the service after installation on macOS, double-click the /applications/TDengine to start the program, or in a terminal, use:

sudo launchctl start com.tdengine.taosd

Then users can use the TDengine CLI to connect the TDengine server. In a terminal, use:

taos

If TDengine CLI connects the server successfully, welcome messages and version info are printed. Otherwise, an error message is shown.

7.3 Run TDengine on Windows

Detailed steps to run on windows

You can start TDengine server on Windows platform with below commands:

.\build\bin\taosd.exe -c test\cfg

In another terminal, use the TDengine CLI to connect the server:

.\build\bin\taos.exe -c test\cfg

option "-c test/cfg" specifies the system configuration file directory.

8. Testing

For how to run different types of tests on TDengine, please see Testing TDengine.

9. Releasing

For the complete list of TDengine Releases, please see Releases.

10. Workflow

TDengine build check workflow can be found in this Github Action. More workflows will be available soon.

11. Coverage

Latest TDengine test coverage report can be found on coveralls.io

How to run the coverage report locally?

To create the test coverage report (in HTML format) locally, please run following commands:

cd tests
bash setup-lcov.sh -v 1.16 && ./run_local_coverage.sh -b main -c task 
# on main branch and run cases in longtimeruning_cases.task 
# for more infomation about options please refer to ./run_local_coverage.sh -h

NOTE: Please note that the -b and -i options will recompile TDengine with the -DCOVER=true option, which may take a amount of time.

12. Contributing

Please follow the contribution guidelines to contribute to TDengine.