README.md

    Build Status Build status Coverage Status CII Best Practices tdengine

    TDengine

    English | 简体中文

    What is TDengine?

    TDengine is an open-sourced big data platform under GNU AGPL v3.0, designed and optimized for the Internet of Things (IoT), Connected Cars, Industrial IoT, and IT Infrastructure and Application Monitoring. Besides the 10x faster time-series database, it provides caching, stream computing, message queuing and other functionalities to reduce the complexity and cost of development and operation.

    • 10x Faster on Insert/Query Speeds: Through the innovative design on storage, on a single-core machine, over 20K requests can be processed, millions of data points can be ingested, and over 10 million data points can be retrieved in a second. It is 10 times faster than other databases.

    • 1/5 Hardware/Cloud Service Costs: Compared with typical big data solutions, less than 1/5 of computing resources are required. Via column-based storage and tuned compression algorithms for different data types, less than 1/10 of storage space is needed.

    • Full Stack for Time-Series Data: By integrating a database with message queuing, caching, and stream computing features together, it is no longer necessary to integrate Kafka/Redis/HBase/Spark or other software. It makes the system architecture much simpler and more robust.

    • Powerful Data Analysis: Whether it is 10 years or one minute ago, data can be queried just by specifying the time range. Data can be aggregated over time, multiple time streams or both. Ad Hoc queries or analyses can be executed via TDengine shell, Python, R or Matlab.

    • Seamless Integration with Other Tools: Telegraf, Grafana, Matlab, R, and other tools can be integrated with TDengine without a line of code. MQTT, OPC, Hadoop, Spark, and many others will be integrated soon.

    • Zero Management, No Learning Curve: It takes only seconds to download, install, and run it successfully; there are no other dependencies. Automatic partitioning on tables or DBs. Standard SQL is used, with C/C++, Python, JDBC, Go and RESTful connectors.

    Documentation

    For user manual, system design and architecture, engineering blogs, refer to TDengine Documentation(中文版请点击这里) for details. The documentation from our website can also be downloaded locally from documentation/tdenginedocs-en or documentation/tdenginedocs-cn.

    Building

    At the moment, TDengine only supports building and running on Linux systems. You can choose to install from packages or from the source code. This quick guide is for installation from the source only.

    To build TDengine, use CMake 2.8.12.x or higher versions in the project directory.

    Install tools

    Ubuntu 16.04 and above & Debian:

    sudo apt-get install -y gcc cmake build-essential git

    Ubuntu 14.04:

    sudo apt-get install -y gcc cmake3 build-essential git binutils-2.26
    export PATH=/usr/lib/binutils-2.26/bin:$PATH

    To compile and package the JDBC driver source code, you should have a Java jdk-8 or higher and Apache Maven 2.7 or higher installed. To install openjdk-8:

    sudo apt-get install -y openjdk-8-jdk

    To install Apache Maven:

    sudo apt-get install -y  maven

    Centos 7:

    sudo yum install -y gcc gcc-c++ make cmake git

    To install openjdk-8:

    sudo yum install -y java-1.8.0-openjdk

    To install Apache Maven:

    sudo yum install -y maven

    Centos 8 & Fedora:

    sudo dnf install -y gcc gcc-c++ make cmake epel-release git

    To install openjdk-8:

    sudo dnf install -y java-1.8.0-openjdk

    To install Apache Maven:

    sudo dnf install -y maven

    Get the source codes

    First of all, you may clone the source codes from github:

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

    The connectors for go & grafana have been moved to separated repositories, so you should run this command in the TDengine directory to install them:

    git submodule update --init --recursive

    Build TDengine

    On Linux platform

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

    TDengine build script can detect the host machine's architecture on X86-64, X86, arm64 and arm32 platform. You can also specify CPUTYPE option like aarch64 or aarch32 too if the detection result is not correct:

    aarch64:

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

    aarch32:

    cmake .. -DCPUTYPE=aarch32 && cmake --build .

    On Windows platform

    If you use the Visual Studio 2013, please open a command window by executing "cmd.exe". Please specify "x86_amd64" for 64 bits Windows or specify "x86" is 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" < x86_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" is 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

    On Mac OS X platform

    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 .

    Installing

    After building successfully, TDengine can be installed by:

    sudo make install

    Users can find more information about directories installed on the system in the directory and files section. Since version 2.0, installing from source code will also configure service management for TDengine. Users can also choose to install from packages for it.

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

    sudo systemctl start taosd

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

    taos

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

    Quick Run

    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:

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

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

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

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

    Try TDengine

    It is easy to run SQL commands from TDengine shell which is the same as other SQL databases.

    create database db;
    use db;
    create table t (ts timestamp, a int);
    insert into t values ('2019-07-15 00:00:00', 1);
    insert into t values ('2019-07-15 01:00:00', 2);
    select * from t;
    drop database db;

    Developing with TDengine

    Official Connectors

    TDengine provides abundant developing tools for users to develop on TDengine. Follow the links below to find your desired connectors and relevant documentation.

    Third Party Connectors

    The TDengine community has also kindly built some of their own connectors! Follow the links below to find the source code for them.

    How to run the test cases and how to add a new test case?

    TDengine's test framework and all test cases are fully open source. Please refer to this document for how to run test and develop new test case.

    TDengine Roadmap

    • Support event-driven stream computing
    • Support user defined functions
    • Support MQTT connection
    • Support OPC connection
    • Support Hadoop, Spark connections
    • Support Tableau and other BI tools

    Contribute to TDengine

    Please follow the contribution guidelines to contribute to the project.

    Join TDengine WeChat Group

    Add WeChat “tdengine” to join the group,you can communicate with other users.

    User List

    If you are using TDengine and feel it helps or you'd like to do some contributions, please add your company to user list and let us know your needs.

    项目简介

    TDengine是涛思数据专为物联网、车联网、工业互联网、IT运维等设计和优化的大数据平台。除核心的快10倍以上的时序数据库功能外,还提供缓存、数据订阅、流式计算等功能,最大程度减少研发和运维的复杂度,且核心代码,包括集群功能全部开源。

    发行版本 19

    ver-2.1.2.0

    全部发行版

    贡献者 42

    全部贡献者

    开发语言

    • C 51.6 %
    • Python 28.0 %
    • Java 9.3 %
    • Shell 5.2 %
    • C++ 1.7 %