Getting Started

With InfluxDB installed, you’re ready to start doing some awesome things. In this section we’ll use the influx command line interface (CLI), which is included in all InfluxDB packages and is a lightweight and simple way to interact with the database. The CLI communicates with InfluxDB directly by making requests to the InfluxDB HTTP API over port 8086 by default.

Note: The database can also be used by making raw HTTP requests. See Writing Data and Querying Data for examples with the curl application.

Creating a database

If you’ve installed InfluxDB locally, the influx command should be available via the command line. Executing influx will start the CLI and automatically connect to the local InfluxDB instance (assuming you have already started the server with service influxdb start or by running influxd directly). The output should look like this:

$ influx
Connected to http://localhost:8086 version 0.13.x
InfluxDB shell 0.13.x
>

Note: The InfluxDB HTTP API runs on port 8086 by default. Therefore, influx will connect to port 8086 and localhost by default. If you need to alter these defaults, run influx --help.

The command line is now ready to take input in the form of the Influx Query Language (a.k.a InfluxQL) statements. To exit the InfluxQL shell, type exit and hit return.

A fresh install of InfluxDB has no databases (apart from the system _internal), so creating one is our first task. You can create a database with the CREATE DATABASE <db-name> InfluxQL statement, where <db-name> is the name of the database you wish to create. Names of databases can contain any unicode character as long as the string is double-quoted. Names can also be left unquoted if they contain only ASCII letters, digits, or underscores and do not begin with a digit.

Throughout this guide, we’ll use the database name mydb:

> CREATE DATABASE mydb
>

Note: After hitting enter, a new prompt appears and nothing else is displayed. In the CLI, this means the statement was executed and there were no errors to display. There will always be an error displayed if something went wrong. No news is good news!

Now that the mydb database is created, we’ll use the SHOW DATABASES statement to display all existing databases:

> SHOW DATABASES
name: databases
---------------
name
_internal
mydb

>

Note: The _internal database is created and used by InfluxDB to store internal runtime metrics. Check it out later to get an interesting look at how InfluxDB is performing under the hood.

Unlike SHOW DATABASES, most InfluxQL statements must operate against a specific database. You may explicitly name the database with each query, but the CLI provides a convenience statement, USE <db-name>, which will automatically set the database for all future requests. For example:

> USE mydb
Using database mydb
>

Now future commands will only be run against the mydb database.

Writing and exploring data

Now that we have a database, InfluxDB is ready to accept queries and writes.

First, a short primer on the datastore. Data in InfluxDB is organized by “time series”, which contain a measured value, like “cpu_load” or “temperature”. Time series have zero to many points, one for each discrete sample of the metric. Points consist of time (a timestamp), a measurement (“cpu_load”, for example), at least one key-value field (the measured value itself, e.g. “value=0.64”, or “temperature=21.2”), and zero to many key-value tags containing any metadata about the value (e.g. “host=server01”, “region=EMEA”, “dc=Frankfurt”).

Conceptually you can think of a measurement as an SQL table, where the primary index is always time. tags and fields are effectively columns in the table. tags are indexed, and fields are not. The difference is that, with InfluxDB, you can have millions of measurements, you don’t have to define schemas up-front, and null values aren’t stored.

Points are written to InfluxDB using the Line Protocol, which follows the following format:

<measurement>[,<tag-key>=<tag-value>...] <field-key>=<field-value>[,<field2-key>=<field2-value>...] [unix-nano-timestamp]

The following lines are all examples of points that can be written to InfluxDB:

cpu,host=serverA,region=us_west value=0.64
payment,device=mobile,product=Notepad,method=credit billed=33,licenses=3i 1434067467100293230
stock,symbol=AAPL bid=127.46,ask=127.48
temperature,machine=unit42,type=assembly external=25,internal=37 1434067467000000000

Note: More information on the line protocol can be found on the Write Syntax page.

To insert a single time-series datapoint into InfluxDB using the CLI, enter INSERT followed by a point:

> INSERT cpu,host=serverA,region=us_west value=0.64
>

A point with the measurement name of cpu and tag host has now been written to the database, with the measured value of 0.64.

Now we will query for the data we just wrote:

> SELECT host, region, value FROM cpu
name: cpu
---------
time		    	                     host     	region   value
2015-10-21T19:28:07.580664347Z  serverA	  us_west	 0.64

>

Note: We did not supply a timestamp when writing our point. When no timestamp is supplied for a point, InfluxDB assigns the local current timestamp when the point is ingested. That means your timestamp will be different.

Let’s try storing another type of data, with two fields in the same measurement:

> INSERT temperature,machine=unit42,type=assembly external=25,internal=37
>

To return all fields and tags with a query, you can use the * operator:

> SELECT * FROM temperature
name: temperature
-----------------
time		                        	 external	  internal	machine	type
2015-10-21T19:28:08.385013942Z  25	        	37     		unit42  assembly

>

InfluxQL has many features and keywords that are not covered here, including support for Go-style regex. For example:

> SELECT * FROM /.*/ LIMIT 1
--
> SELECT * FROM cpu_load_short
--
> SELECT * FROM cpu_load_short WHERE value > 0.9

This is all you need to know to write data into InfluxDB and query it back. To learn more about the InfluxDB write protocol, check out the guide on Writing Data. To further explore the query language, check out the guide on Querying Data. For more information on InfluxDB concepts, check out the Key Concepts page.