排名前十的时序数据库[通俗易懂]

排名前十的时序数据库[通俗易懂]时序数据库全称为时间序列数据库。时间序列数据库主要用于指处理带时间标签(按照时间的顺序变化,即时间序列化)的数据,带时间标签的数据也称为时间序列数据。时序数据的兴起还是榜上了物联网的大风。物联网(InternetofThings,简称IOT)是指通过各种信息传感器实时采集任何需要管理设备的信息,并进行管理。物联网的基础数据具有数据量大、结构单一、时间属性强、查询简单等特点,传统的关系型数据库在面对物联网数据时,显得应对发力,基本上属于功能过剩但性能不足。目前最新的DB-Engine上时序数据库排名如下

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时序数据库全称为时间序列数据库。时间序列数据库主要用于指处理带时间标签(按照时间的顺序变化,即时间序列化)的数据,带时间标签的数据也称为时间序列数据。时序数据的兴起还是榜上了物联网的大风。物联网(Internet of Things,简称IOT)是指通过各种信息传感器实时采集任何需要管理设备的信息,并进行管理。物联网的基础数据具有数据量大、结构单一、时间属性强、查询简单等特点,传统的关系型数据库在面对物联网数据时,显得应对发力,基本上属于功能过剩但性能不足。
目前最新的DB-Engine上时序数据库排名如下:

在这里插入图片描述

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

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