• 开源时序数据选型


    一、
    1.apache的IoTDB
    https://iotdb.apache.org/
    2.InfluxDB
    https://www.influxdata.com/
    3.timescale:TimescaleDB基于PostgreSQL的时序数据库插件,完全继承了PostgreSQL的功能
    https://www.timescale.com/
    4.TDengine
    https://www.taosdata.com/cn/

    二、时序数据库比对
    https://www.cnblogs.com/dhcn/p/10370032.html

    三、时序数据库排行
    在这里插入图片描述
    四时序数据库排行介绍

    1.InfluxDB
    2013
    DBMS for storing time series, events and metrics
    www.influxdata.com
    
    InfluxDB empowers developers to build IoT, analytics and monitoring software. It is purpose-built to handle the massive volumes and countless sources of time-stamped data produced by sensors, applications and infrastructure.
    
    2.KDb+
    2000
    High performance Time Series DBMS
    kx.com
    
    3.Prometheus
    2015
    Open-source TimeSeries DBMS and monitoring system
    prometheus.io/
    
    Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. Since its inception in 2012, many companies and organizations have adopted Prometheus, and the project has a very active developer and user community. It is now a standalone open source project and maintained independently of any company. To emphasize this, and to clarify the project’s governance structure, Prometheus joined the Cloud Native Computing Foundation in 2016 as the second hosted project, after Kubernetes.
    
    4.Graphite
    2006
    Data logging and graphing tool for time series data
    github.com/­graphite-project/­graphite-web
    
    5.RRDtool
    1999
    Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.
    oss.oetiker.ch/­rrdtool
    RRDtool is the OpenSource industry standard, high performance data logging and graphing system for time series data. RRDtool can be easily integrated in shell scripts, perl, python, ruby, lua or tcl applications.
    
    6.TimescaleDB
    2017
    A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
    www.timescale.com
    
    7.Apache Druid
    2012
    Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data
    druid.apache.org
    
    8.Fauna
    2014
    Fauna (previously named FaunaDB) provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.
    fauna.com
    
    9.OpenTSDB
    2011
    Scalable Time Series DBMS based on HBase
    opentsdb.net
    
    10.GridDB
    2013
    Scalable in-memory time series database optimized for IoT and Big Data
    griddb.net
    
    GridDB is an innovative solution to solve these complex problems. The foundation of GridDB’s principles is based upon offering a versatile data store that is optimized for IoT, provides high scalability, is tuned for high performance, and ensures high reliability.
    
    11.DolphinDB
    2018
    Time Series DBMS for big data, integrated with a lightweight distributed computing framework and a vector programming language
    www.dolphindb.com
    
    DolphinDB is a high performance time-series database. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. DolphinDB offers operational simplicity, scalability, fault tolerance, and concurrency.
    
    12.KairosDB
    2013
    Distributed Time Series DBMS based on Cassandra or H2
    github.com/­kairosdb/­kairosdb
    
    原文链接:https://blog.csdn.net/weixin_43700866/article/details/114914866
    

    安装:
    1.InfluxDB
    文档:https://docs.influxdata.com/influxdb/v2.0/install/?t=Linux
    wget https://dl.influxdata.com/influxdb/releases/influxdb2-2.0.8.x86_64.rpm
    sudo yum localinstall influxdb2-2.0.8.x86_64.rpm

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  • 原文地址:https://www.cnblogs.com/InternetJava/p/15731300.html
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