InfluxDB is an opensource time series database for handling events, monitoring, metrics, the Internet of Things and real-time analytics. It is developed by InfluxData in the Go language. You can find more information on wikipedia.

To install it on Debian you simply use apt-get:

# apt-cache search influxdb 
golang-github-influxdb-enterprise-client-dev - Golang client for speaking to the InfluxDB Enterprise application
golang-github-influxdb-usage-client-dev - library for speaking to the InfluxDB Anonymous Usage Reporting API
golang-gopkg-alexcesaro-statsd.v1-dev - simple and efficient Golang StatsD client
golang-github-influxdb-influxdb-dev - Scalable datastore for metrics, events, and real-time analytics. Dev package
influxdb - Scalable datastore for metrics, events, and real-time analytics
influxdb-client - command line interface for InfluxDB
influxdb-dev - Transitional package for golang-github-influxdb-influxdb-dev
ruby-influxdb - library for InfluxDB

To install:

# apt-get install influxdb influxdb-client

To test that it is running:

# influx
Visit https://enterprise.influxdata.com to register for updates, InfluxDB server management, and monitoring.
Connected to http://localhost:8086 version 1.0.2
InfluxDB shell version: 1.0.2
>

To create a database called mydb:

> create database mydb

List the databases:

> show databases
name: databases
---------------
name
_internal
mydb

Insert data and query it in the mydb database:

> use mydb
Using database mydb
> INSERT cpu,host=ServerA,region=us_west value=0.64
> SELECT host, region, value FROM cpu
name: cpu
---------
time                   host         region value
1498340879346347895 ServerA us_west 0.64

As you can see, the primary key of the data is always the time.

Now a small test with Python.

To install the library in Python:

# pip3 install influxdb

We have the following script:



#!/usr/bin/env python3





#Se importa influxdb


from influxdb import InfluxDBClient





#Se define un json con los datos a insertar


json_body = [


    {


        "measurement": "cpu_load_short",


        "tags": {


            "host": "server01",


            "region": "us-west"


        },


        "time": "2009-11-10T23:00:00Z",


        "fields": {


            "value": 0.64


        }


    },


    {


        "measurement": "cpu_load_short",


        "tags": {


            "host": "server02",


            "region": "us-west"


        },


        "time": "2009-12-10T23:00:00Z",


        "fields": {


            "value": 0.65


        }


    }


]


#Se conecta a la base de datos


client = InfluxDBClient('localhost', 8086, 'root', 'root', 'mydb')


#Se crea la base de datos mydb


client.create_database('mydb')





#Se inserta los datos


client.write_points(json_body)


#Se consulta y se muestra en pantalla


result = client.query('select value from cpu_load_short;')


print("Result: {0}".format(result))

When the script is run, it returns the following:

./prueba-influxdb.py 
Result: ResultSet({'('cpu_load_short', None)': [{'value': 0.64, 'time': '2009-11-10T23:00:00Z'}, {'value': 0.65, 'time': '2009-12-10T23:00:00Z'}]})

Or from the influxdb client:

> use mydb
Using database mydb
> select value from cpu_load_short;
name: cpu_load_short
--------------------
time   value
1257894000000000000 0.64
1260486000000000000 0.65

As shown, the key that drives the queries is the time.

For more information, see the following links:

  • Grafana, influxdb and python.
  • influxdb-python and its documentation.
  • influxdata documentation.
  • Influxdata platform

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