Documentation

Calculate the rate of change

This page documents an earlier version of InfluxDB OSS. InfluxDB 3 Core is the latest stable version.

Use derivative() to calculate the rate of change between subsequent values or aggregate.rate() to calculate the average rate of change per window of time. If time between points varies, these functions normalize points to a common time interval making values easily comparable.

Rate of change between subsequent values

Use the derivative() function to calculate the rate of change per unit of time between subsequent non-null values.

data
    |> derivative(unit: 1s)

By default, derivative() returns only positive derivative values and replaces negative values with null. Calculated values are returned as floats.

Given the following input:

_time_value
2020-01-01T00:00:00Z250
2020-01-01T00:04:00Z160
2020-01-01T00:12:00Z150
2020-01-01T00:19:00Z220
2020-01-01T00:32:00Z200
2020-01-01T00:51:00Z290
2020-01-01T01:00:00Z340

derivative(unit: 1m) returns:

_time_value
2020-01-01T00:04:00Z
2020-01-01T00:12:00Z
2020-01-01T00:19:00Z10.0
2020-01-01T00:32:00Z
2020-01-01T00:51:00Z4.74
2020-01-01T01:00:00Z5.56

Results represent the rate of change per minute between subsequent values with negative values set to null.

Return negative derivative values

To return negative derivative values, set the nonNegative parameter to false,

Given the following input:

_time_value
2020-01-01T00:00:00Z250
2020-01-01T00:04:00Z160
2020-01-01T00:12:00Z150
2020-01-01T00:19:00Z220
2020-01-01T00:32:00Z200
2020-01-01T00:51:00Z290
2020-01-01T01:00:00Z340

The following returns:

|> derivative(unit: 1m, nonNegative: false)
_time_value
2020-01-01T00:04:00Z-22.5
2020-01-01T00:12:00Z-1.25
2020-01-01T00:19:00Z10.0
2020-01-01T00:32:00Z-1.54
2020-01-01T00:51:00Z4.74
2020-01-01T01:00:00Z5.56

Results represent the rate of change per minute between subsequent values and include negative values.

Average rate of change per window of time

Use the aggregate.rate() function to calculate the average rate of change per window of time.

import "experimental/aggregate"

data
    |> aggregate.rate(
        every: 1m,
        unit: 1s,
        groupColumns: ["tag1", "tag2"],
    )

aggregate.rate() returns the average rate of change (as a float) per unit for time intervals defined by every. Negative values are replaced with null.

aggregate.rate() does not support nonNegative: false.

Given the following input:

_time_value
2020-01-01T00:00:00Z250
2020-01-01T00:04:00Z160
2020-01-01T00:12:00Z150
2020-01-01T00:19:00Z220
2020-01-01T00:32:00Z200
2020-01-01T00:51:00Z290
2020-01-01T01:00:00Z340

The following returns:

|> aggregate.rate(
    every: 20m,
    unit: 1m,
)
_time_value
2020-01-01T00:20:00Z10.00
2020-01-01T00:40:00Z
2020-01-01T01:00:00Z4.74
2020-01-01T01:20:00Z5.56

Results represent the average change rate per minute of every 20 minute interval with negative values set to null. Timestamps represent the right bound of the time window used to average values.


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New in InfluxDB 3.5

Key enhancements in InfluxDB 3.5 and the InfluxDB 3 Explorer 1.3.

See the Blog Post

InfluxDB 3.5 is now available for both Core and Enterprise, introducing custom plugin repository support, enhanced operational visibility with queryable CLI parameters and manual node management, stronger security controls, and general performance improvements.

InfluxDB 3 Explorer 1.3 brings powerful new capabilities including Dashboards (beta) for saving and organizing your favorite queries, and cache querying for instant access to Last Value and Distinct Value caches—making Explorer a more comprehensive workspace for time series monitoring and analysis.

For more information, check out:

InfluxDB Docker latest tag changing to InfluxDB 3 Core

On November 3, 2025, the latest tag for InfluxDB Docker images will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments.

If using Docker to install and run InfluxDB, the latest tag will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments. For example, if using Docker to run InfluxDB v2, replace the latest version tag with a specific version tag in your Docker pull command–for example:

docker pull influxdb:2