How to Query Data in InfluxDB – Step-by-Step Tutorial

How to Query Data in InfluxDB: A Step-by-Step Guide

InfluxDB is a popular open-source time-series database designed for handling high write and query loads with ease. If you are working with time-series data — such as metrics, events, or sensor data — knowing how to query this data effectively is essential. In this tutorial, we walk you through the basics of querying data in InfluxDB, covering both the Influx Query Language (InfluxQL) and the newer Flux language.

Prerequisites

An active InfluxDB server setup or access to an InfluxDB instance.
Basic knowledge of databases and time-series concepts.
InfluxDB CLI or UI (InfluxDB Cloud or OSS) access to run queries.

Understanding InfluxDB Query Languages

InfluxDB supports two main languages for querying data:

InfluxQL: A SQL-like query language originally used in InfluxDB. Easy for those familiar with SQL.
Flux: A more powerful and flexible scripting and query language designed for complex analytics and data transformation.

Step 1: Writing Basic InfluxQL Queries

InfluxQL queries resemble SQL and are structured to read data from measurements where fields and tags describe the data points.

Example: Querying All Data from a Measurement

SELECT * FROM "temperature"

This returns all fields from the temperature measurement.

Filtering by Time Range

SELECT mean("value") FROM "temperature" WHERE time > now() - 1h GROUP BY time(10m)

This gets the average temperature over the past hour grouped into 10-minute windows.

Step 2: Using Flux for Advanced Queries

Flux allows more control and can join data from multiple buckets, filter more flexibly, and perform transformations.

Basic Flux Query Example

from(bucket: "sensor_data")
  |> range(start: -1h)
  |> filter(fn: (r) => r._measurement == "temperature")
  |> mean()

This queries the temperature measurement in the sensor_data bucket for the last hour and calculates the mean.

Filtering on Tags and Fields

from(bucket: "sensor_data")
  |> range(start: -12h)
  |> filter(fn: (r) => r._measurement == "temperature" and r.location == "room1")
  |> filter(fn: (r) => r._field == "value")

Step 3: Querying with the InfluxDB UI or CLI

You can execute these queries directly in the InfluxDB UI, which provides instant feedback and graphs. Alternatively, use the influx CLI tool:

influx query 'from(bucket: "sensor_data")
  |> range(start: -30m)
  |> filter(fn: (r) => r._measurement == "cpu")
  |> mean()'

Troubleshooting Common Issues

Empty query results: Verify your time range and measurements exist.
Syntax errors: Double-check your Flux or InfluxQL syntax, especially around quotes and parentheses.
Permissions: Ensure your user has read access to the target bucket or database.

Summary Checklist

Understand whether to use InfluxQL or Flux based on your needs.
Begin with simple SELECT queries or basic Flux scripts.
Filter data by time range and tags/fields appropriately.
Use the InfluxDB UI or CLI for querying and visualization.
Check permissions and syntax when queries fail.

For more InfluxDB fundamentals, you might find our tutorial on how to write data in InfluxDB helpful as it complements querying by explaining how data is stored.

Querying efficiently in InfluxDB opens up powerful possibilities for analyzing time-series data and making data-driven decisions in real time. Start experimenting with these queries today!