Grafana ships with a built-in PostgreSQL data source plugin that allows you to query and visualize data from a PostgreSQL compatible database.
For instructions on how to add a data source to Grafana, refer to the [administration documentation]({{< relref "../../administration/data-source-management/" >}}).
Only users with the organization administrator role can add data sources.
Administrators can also [configure the data source via YAML]({{< relref "#provision-the-data-source" >}}) with Grafana's provisioning system.
| **Name** | The data source name. This is how you refer to the data source in panels and queries. |
| **Default** | Default data source means that it will be pre-selected for new panels. |
| **Host** | The IP address/hostname and optional port of your PostgreSQL instance. _Do not_ include the database name. The connection string for connecting to Postgres will not be correct and it may cause errors. |
| **Database** | Name of your PostgreSQL database. |
| **User** | Database user's login/username |
| **Password** | Database user's password |
| **SSL Mode** | Determines whether or with what priority a secure SSL TCP/IP connection will be negotiated with the server. When SSL Mode is disabled, SSL Method and Auth Details would not be visible. |
| **SSL Auth Details Method** | Determines whether the SSL Auth details will be configured as a file path or file content. Grafana v7.5+ |
| **SSL Auth Details Value** | File path or file content of SSL root certificate, client certificate and client key |
| **Max open** | The maximum number of open connections to the database, default `100` (Grafana v5.4+). |
| **Max idle** | The maximum number of connections in the idle connection pool, default `100` (Grafana v5.4+). |
| **Auto (max idle)** | If set will set the maximum number of idle connections to the number of maximum open connections (Grafana v9.5.1+). Default is `true`. |
| **Max lifetime** | The maximum amount of time in seconds a connection may be reused, default `14400`/4 hours (Grafana v5.4+). |
| **Version** | Determines which functions are available in the query builder (only available in Grafana 5.3+). |
| **TimescaleDB** | A time-series database built as a PostgreSQL extension. When enabled, Grafana uses `time_bucket` in the `$__timeGroup` macro to display TimescaleDB specific aggregate functions in the query builder (only available in Grafana 5.3+). For more information, see [TimescaleDB documentation](https://docs.timescale.com/timescaledb/latest/tutorials/grafana/grafana-timescalecloud/#connect-timescaledb-and-grafana). |
A lower limit for the [$__interval]({{< relref "../../dashboards/variables/add-template-variables/#__interval" >}}) and [$__interval_ms]({{< relref "../../dashboards/variables/add-template-variables/#__interval_ms" >}}) variables.
This option can also be overridden/configured in a dashboard panel under data source options. It's important to note that this value **needs** to be formatted as a
number followed by a valid time identifier, e.g. `1m` (1 minute) or `30s` (30 seconds). The following time identifiers are supported:
The PostgreSQL query builder is available when editing a panel using a PostgreSQL data source. The built query can be run by pressing the `Run query` button in the top right corner of the editor.
The response from PostgreSQL can be formatted as either a table or as a time series. To use the time series format one of the columns must be named `time`.
To group the results by column, flip the group switch at the top of the editor. You can then choose which column to group the results by. The group by clause can be removed by pressing the X button.
It's now possible to configure data sources using config files with Grafana's provisioning system. You can read more about how it works and all the settings you can set for data sources on the [provisioning docs page]({{< relref "../../administration/provisioning#datasources" >}}).
To make advanced queries, switch to the code editor by clicking `code` in the top right corner of the editor. The code editor support autocompletion of tables, columns, SQL keywords, standard sql functions, Grafana template variables and Grafana macros. Columns cannot be completed before a table has been specified.
| `$__time(dateColumn)` | Will be replaced by an expression to convert to a UNIX timestamp and rename the column to `time_sec`. For example, _UNIX_TIMESTAMP(dateColumn) as time_sec_ |
| `$__timeEpoch(dateColumn)` | Will be replaced by an expression to convert to a UNIX timestamp and rename the column to `time_sec`. For example, _UNIX_TIMESTAMP(dateColumn) as time_sec_ |
| `$__timeFilter(dateColumn)` | Will be replaced by a time range filter using the specified column name. For example, _dateColumn BETWEEN FROM_UNIXTIME(1494410783) AND FROM_UNIXTIME(1494410983)_ |
| `$__timeFrom()` | Will be replaced by the start of the currently active time selection. For example, _FROM_UNIXTIME(1494410783)_ |
| `$__timeTo()` | Will be replaced by the end of the currently active time selection. For example, _FROM_UNIXTIME(1494410983)_ |
| `$__timeGroup(dateColumn,'5m')` | Will be replaced by an expression usable in GROUP BY clause. For example, *cast(cast(UNIX_TIMESTAMP(dateColumn)/(300) as signed)*300 as signed),\* |
| `$__timeGroup(dateColumn,'5m', 0)` | Same as above but with a fill parameter so missing points in that series will be added by grafana and 0 will be used as value. |
| `$__timeGroup(dateColumn,'5m', NULL)` | Same as above but NULL will be used as value for missing points. |
| `$__timeGroup(dateColumn,'5m', previous)` | Same as above but the previous value in that series will be used as fill value if no value has been seen yet NULL will be used (only available in Grafana 5.3+). |
| `$__timeGroupAlias(dateColumn,'5m')` | Will be replaced identical to $\_\_timeGroup but with an added column alias (only available in Grafana 5.3+). |
| `$__unixEpochFilter(dateColumn)` | Will be replaced by a time range filter using the specified column name with times represented as Unix timestamp. For example, _dateColumn > 1494410783 AND dateColumn < 1494497183_ |
| `$__unixEpochFrom()` | Will be replaced by the start of the currently active time selection as Unix timestamp. For example, _1494410783_ |
| `$__unixEpochTo()` | Will be replaced by the end of the currently active time selection as Unix timestamp. For example, _1494497183_ |
| `$__unixEpochNanoFilter(dateColumn)` | Will be replaced by a time range filter using the specified column name with times represented as nanosecond timestamp. For example, _dateColumn > 1494410783152415214 AND dateColumn < 1494497183142514872_ |
| `$__unixEpochNanoFrom()` | Will be replaced by the start of the currently active time selection as nanosecond timestamp. For example, _1494410783152415214_ |
| `$__unixEpochNanoTo()` | Will be replaced by the end of the currently active time selection as nanosecond timestamp. For example, _1494497183142514872_ |
| `$__unixEpochGroup(dateColumn,'5m', [fillmode])` | Same as $\_\_timeGroup but for times stored as Unix timestamp (only available in Grafana 5.3+). |
| `$__unixEpochGroupAlias(dateColumn,'5m', [fillmode])` | Same as above but also adds a column alias (only available in Grafana 5.3+). |
We plan to add many more macros. If you have suggestions for what macros you would like to see, please [open an issue](https://github.com/grafana/grafana) in our GitHub repo.
If the `Format as` query option is set to `Table` then you can basically do any type of SQL query. The table panel will automatically show the results of whatever columns and rows your query returns.
If you set Format as to _Time series_, then the query must have a column named time that returns either a SQL datetime or any numeric datatype representing Unix epoch in seconds. In addition, result sets of time series queries must be sorted by time for panels to properly visualize the result.
A time series query result is returned in a [wide data frame format]({{< relref "../../developers/plugins/data-frames#wide-format" >}}). Any column except time or of type string transforms into value fields in the data frame query result. Any string column transforms into field labels in the data frame query result.
> For backward compatibility, there's an exception to the above rule for queries that return three columns including a string column named metric. Instead of transforming the metric column into field labels, it becomes the field name, and then the series name is formatted as the value of the metric column. See the example with the metric column below.
To optionally customize the default series name formatting, refer to [Standard options definitions]({{< relref "../../panels-visualizations/configure-standard-options#display-name" >}}).
Given the data frame result in the following example and using the graph panel, you will get two series named _value 10.0.1.1_ and _value 10.0.1.2_. To render the series with a name of _10.0.1.1_ and _10.0.1.2_ , use a [Standard options definitions]({{< relref "../../panels-visualizations/configure-standard-options#display-name" >}}) display value of `${__field.labels.hostname}`.
Instead of hard-coding things like server, application and sensor name in your metric queries you can use variables in their place. Variables are shown as dropdown select boxes at the top of the dashboard. These dropdowns make it easy to change the data being displayed in your dashboard.
Refer to [Templates and variables]({{< relref "../../dashboards/variables" >}}) for an introduction to the templating feature and the different types of template variables.
For example, you can have a variable that contains all values for the `hostname` column in a table if you specify a query like this in the templating variable _Query_ setting.
A query can return multiple columns and Grafana will automatically create a list from them. For example, the query below will return a list with values from `hostname` and `hostname2`.
```sql
SELECT host.hostname, other_host.hostname2 FROM host JOIN other_host ON host.city = other_host.city
To use time range dependent macros like `$__timeFilter(column)` in your query the refresh mode of the template variable needs to be set to _On Time Range Change_.
Another option is a query that can create a key/value variable. The query should return two columns that are named `__text` and `__value`. The `__text` column value should be unique (if it is not unique then the first value is used). The options in the dropdown will have a text and value that allows you to have a friendly name as text and an id as the value. An example query with `hostname` as the text and `id` as the value:
```sql
SELECT hostname AS __text, id AS __value FROM host
the hosts variable only show hosts from the current selected region with a query like this (if `region` is a multi-value variable then use the `IN` comparison operator rather than `=` to match against multiple values):
```sql
SELECT hostname FROM host WHERE region IN($region)
> Important that you surround the `__searchFilter` expression with quotes as Grafana does not do this for you.
The example below shows how to use `__searchFilter` as part of the query field to enable searching for `hostname` while the user types in the dropdown select box.
From Grafana 4.3.0 to 4.6.0, template variables are always quoted automatically. If your template variables are strings, do not wrap them in quotes in where clauses.
Grafana automatically creates a quoted, comma-separated string for multi-value variables. For example: if `server01` and `server02` are selected then it will be formatted as: `'server01', 'server02'`. To disable quoting, use the csv formatting option for variables:
Read more about variable formatting options in the [Variables]({{< relref "../../dashboards/variables/variable-syntax#advanced-variable-format-options" >}}) documentation.
[Annotations]({{< relref "../../dashboards/build-dashboards/annotate-visualizations" >}}) allow you to overlay rich event information on top of graphs. You add annotation queries via the Dashboard menu / Annotations view.
