docs-v2/content/flux/v0/write-data/sql/_index.md

title	list_title	description	menu	weight	related	list_code_example
Write to SQL databases	SQL databases	Use [`sql.to()`](/flux/v0/stdlib/sql/to/) to write data to SQL databases with Flux.	flux_v0 name parent identifier SQL databases Write to data sources write-to-sql	102	/flux/v0/stdlib/sql/to/	```js import "sql" sql.to( driverName: "postgres", dataSourceName: "postgresql://user:password@localhost", table: "ExampleTable", batchSize: 10000, ) ```

Use sql.to() to write data to SQL databases with Flux.

• Databases
• Drivers
• Data source names
  • Store sensitive credentials as secrets
• Data structure
  • Column data types
• Example

Databases

sql.to() supports the following SQL databases:

{{< children type="list" >}}

Drivers

sql.to() uses Go SQL drivers in the Go sql package to connect to SQL databases. The following drivers are available:

• bigquery
• hdb
• mysql
• postgres
• snowflake
• sqlite3
• sqlserver

Data source names

Each SQL driver supports unique data source name (DSN) syntaxes (also known as connection strings). See the database guides for information about DSNs for each driver.

Store sensitive credentials as secrets

If using InfluxDB Cloud or InfluxDB OSS 2.x, we recommend storing DSN credentials as InfluxDB secrets. Use secrets.get() to retrieve a secret from the InfluxDB secrets API.

import "sql"
import "influxdata/influxdb/secrets"

username = secrets.get(key: "POSTGRES_USER")
password = secrets.get(key: "POSTGRES_PASS")

sql.to(
    driverName: "postgres",
    dataSourceName: "postgresql://${username}:${password}@localhost:5432",
    table: "example_table",
)

Data Structure

sql.to() ungroups all rows into a single table and writes all existing columns as the specified destination table. If the destination table doesn't exist, sql.to() attempts to create it.

{{% note %}}

Column data types

Each sql.to() driver converts Flux basic data types to corresponding data types supported by the target database. See the database guides for information about data type conversions. {{% /note %}}

Example

Given the following following stream of tables:

data

_time	tag	_value
2021-01-01T00:00:00Z	t1	-2
2021-01-01T00:00:10Z	t1	10
2021-01-01T00:00:20Z	t1	7

_time	tag	_value
2021-01-01T00:00:00Z	t2	19
2021-01-01T00:00:10Z	t2	4
2021-01-01T00:00:20Z	t2	-3

Flux script

import "sql"

data
    |> sql.to(
        driverName: "mysql",
        dataSourceName: "username:passwOrd@tcp(localhost:3306)/db",
        table: "exampleTable"
    )

SQL output

_time	tag	_value
2021-01-01 00:00:00	t1	-2
2021-01-01 00:00:10	t1	10
2021-01-01 00:00:20	t1	7
2021-01-01 00:00:00	t2	19
2021-01-01 00:00:10	t2	4
2021-01-01 00:00:20	t2	-3