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+---
+title: Use SQL data
+seotitle: Use SQL data with InfluxDB
+description: >
+  placeholder
+v2.0/tags: [query, flux, sql]
+menu:
+  v2_0:
+    parent: How-to guides
+weight: 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
+
+
+```js
+import "sql"
+
+sensorInfo = sql.from(
+  driver: "postgres",
+  driverName: "",
+  query: ""
+)
+
+sensorMetrics = from(bucket: "sensors" )
+  |> range(start: -1d)
+
+```