Run SQL queries and send the results to Geckoboard Datasets
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SQL-Dataset, by Geckoboard

Quickly and easily send data from Microsoft SQL Server, MySQL, Postgres and SQLite databases to Geckoboard Datasets.

SQL-Dataset is a command line app that takes the hassle out of integrating your database with Geckoboard. Rather than having to work with client libraries and write a bunch of code to connect to and query your database, with SQL-Dataset all you need to do is fill out a simple config file.

SQL-Dataset is available for macOS, Linux, and Windows.


1. Download the app

Make it executable (macOS / Linux)

On macOS and Linux you'll need to open a terminal and run chmod u+x path/to/file (replacing path/to/file with the actual path to your downloaded app) in order to make the app executable.

2. Create a config file

SQL-Datasets works by reading all of the information it needs from a YAML file. We've prepared an example one for you so you can get started quickly. The fields are fairly self-explanatory, but you can learn more about them below.

3. Run the script

Make sure that the SQL-Dataset app and your config file are in the same folder, then from the command line navigate to that folder and run

./sql-dataset -config config.yml

Where config.yml is the name of your config file. Once you see confirmation that everything ran successfully, head over to Geckoboard and start using your new Dataset to build widgets!

Building your config file

Here's what an example config file looks like:

geckoboard_api_key: your_api_key
 driver: mysql
 host: xxxx
 port: xxxx
 username: xxxx
 password: xxxx
 name: xxxx
  ca_file: xxxx
  key_file: xxxx
  cert_file: xxxx
  ssl_mode: xxxx
refresh_time_sec: 60
 - name:
   update_type: replace
   sql: >
    SELECT 1, 0.34, source
    FROM table
    - type: number
      name: Signups
    - type: percentage
      name: Conversion rate
    - type: string
      name: Source

Environment variables

If you wish, you can provide any of geckoboard_api_key, host, port, username, password and (database) name as environment variables with the syntax "{{ YOUR_CUSTOM_ENV }}". Make sure to keep the quotes in there! For example:

geckoboard_api_key: "{{ GB_API_KEY }}"


Hopefully this is obvious, but this is where your Geckoboard API key goes. You can find yours here.


Enter the type of database you're connecting to in the driver field. SQL-Dataset supports:

  • mssql
  • mysql
  • postgres
  • sqlite

If you'd like to see support for another type of database, please raise a support ticket or, if you're technically inclined, make the change and submit a pull request!

Only three parameters are required:

  • driver
  • username
  • name

The other attributes, such as host and port, will default to their driver-specific values unless overridden.


If your database requires a CA cert or a x509 key/cert pair, you can supply this in tls_config under the database key.

 ca_file: /path/to/file.pem
 key_file: /path/to/file.key
 cert_file: /path/to/cert.crt
 ssl_mode: (optional)

The possible values for ssl_mode depend on the database you're using:

  • MSSQL: disable, false, true - try disable option if you experience connection issues
  • MySQL: true, skip-verify
  • Postgres: disable, require, verify-ca, verify-full
  • SQLite: N/A

A note on user permissions

We strongly recommend that the user account you use with SQL-Dataset has the lowest level of permission necessary. For example, one which is only permitted to perform SELECT statements on the tables you're going to be using. Like any SQL program, SQL-Dataset will run any query you give it, which includes destructive operations such as overwriting existing data, removing records, and dropping tables. We accept no responsibility for any adverse changes to your database due to accidentally running such a query.


Once started, SQL-Dataset can run your queries periodically and push the results to Geckoboard. Use this field to specify the time, in seconds, between refreshes.

If you do not wish for SQL-Dataset to run on a schedule, omit this option from your config.


Here's where the magic happens - specify the SQL queries you want to run, and the Datasets you want to push their results into.

  • name: The name of your Dataset
  • sql: Your SQL query
  • fields: The schema of the Dataset into which the results of your SQL query will be parsed
  • update_type: Either replace, which overwrites the contents of the Dataset with new data on each update, or append, which merges the latest update with your existing data.
  • unique_by: An optional array of one or more field names whose values will be unique across all your records. When using the append update method, the fields in unique_by will be used to determine whether new data should update any existing records.


A Dataset can hold up to 10 fields. The fields you declare should map directly to the columns that result from your SELECT query, in the same order.

For example:

sql: SELECT date, orders, refunds FROM sales
 - name: Date
   type: date
 - name: Orders
   type: number
 - name: Refunds
   type: number

SQL-Dataset supports all of the field types supported by the Datasets API:

  • date
  • datetime
  • number
  • percentage
  • string
  • money

The money field type requires a currency_code to be provided:

 - name: MRR
   type: money
   currency_code: USD

Numeric field types can support null values. For a field to support this, pass the optional key:

 - name: A field which might be NULL
   type: number
   optional: true

The Datasets API requires both a name and a key for each field, but SQL-Dataset will infer a key for you. Sometimes, however, the inferred key might not be permitted by the API. If you encounter such a case, you can supply a specific key value for that field.

 - name: Your awesome field
   key: some_unique_key
   type: number