docs-v2/content/v2.0/query-data/guides/use-sql.md

title	seotitle	description	v2.0/tags	menu	weight
Use SQL data	Use SQL data with InfluxDB	placeholder	query flux sql	v2_0 parent How-to guides	210

• Import Flux's sql package and use sql.from to query data from a SQL database such as Postgres or MySQL.

Benefits

• Some data schemas are better suited for SQL databases. With the ability to query a SQL data source, you can store SQL-suited data there and join it with your time series data. This allows you to reduce your InfluxDB schema complexity and improve performance.

Use cases

Reduce cardinality by storing tag data in a SQL data source

High series cardinality can lead to high memory usage, higher hardware costs, and impact the overall performance of InfluxDB. The primary culprit behind cardinality is unique tag values. Using a SQL data source, you can offload much of your tag data to the SQL database. As long as you have at least one common tag on which to join in InfluxDB, that tag data can still be associated data in InfluxDB.

For example:

Join relation data with time series data

• Sensor data with relational sensor information
  • SensorID
  • Name
  • Type
  • Location
  • Model
• Sensor metrics stored in InfluxDB, each with a sensorID tag. Each type of sensor metric is stored in a different measurement.
  • air_quality
    • temperature
    • humidity
    • co2
    • methane
  • light
    • uv

import "sql"

sensorInfo = sql.from(
  driver: "postgres",
  driverName: "",
  query: ""
)

sensorMetrics = from(bucket: "sensors" )
  |> range(start: -1d)