MySQL is an open-source relational database management system hosted either in the cloud or on-premise.
# Supported editions
All editions of MySQL are supported.
# How to connect to MySQL on Workato
The MySQL connector uses basic authentication to authenticate with MySQL.
|Connection name||Give this MySQL connection a unique name that identifies which MySQL instance it is connected to.|
|On-prem secure agent||Choose an on-premise agent if your database is running in a network that does not allow direct connection. Before attempting to connect, make sure you have an active on-premise agent. Refer to the On-premise agent guide for more information.|
|Username||Username to connect to MySQL.|
|Password||Password to connect to MySQL.|
|Host||URL of your hosted server.|
|Port||Port number that your server is running on, typically 3306.|
|Database||Name of the MySQL database you wish to connect to.|
|Advanced Settings||Contains advanced connection settings such as improved datetime handling and ability to set database timezone.|
# Improved datetime handling
The SQL Server connector now has the option to utilise improved handling of datetime, datetime2 and datetimeoffset datatype. This can be enabled in the connection settings of each SQL server connection. This defaults to
Yes for all new connections and defaults to UTC timezones. Change this to the local timezone of your database if needed. This affects all actions that insert rows into MySQL.
There are various timezone settings in MySQL. If no changes are made, your MySQL system timezone should be the same as your global timezone and set to UTC.
Summary of behaviour
|Datatype||Workato input||Improved datetime handling set to false/unselected||Improved datetime handling set to true|
|date||Time with no TZ||Workato workspace timezone assumed. Converted to UTC before insertion||No TZ assumed. Inserted as is|
|date||Time with TZ||Converted to UTC before insertion||Converted to database timezone in connection setting timezone before insertion|
|datetime||Time with no TZ||Workato workspace timezone assumed. Converted to UTC before insertion.||No TZ assumed. Inserted as is|
|datetime||Time with TZ||Converted to UTC before insertion.||Converted to database timezone in connection setting timezone before insertion|
|timestamp||Time with no TZ||Workato workspace timezone assumed. Converted to UTC before insertion with +00:00 tz||No TZ assumed. Inserted as is|
|timestamp||Time with TZ||Converted to UTC before insertion||Converted to database timezone in connection setting timezone before insertion|
When using the calendar datepicker for date/datetime/timestamp fields, times are defined using your Workato workspace timezone.
# Permissions required to connect
At minimum, the database user account must be granted
SELECT permission to the database specified in the connection.
If we are trying to connect to a named database (
HR_PROD) in a MySQL instance, using a new database user
workato, the following example queries can be used.
First, create a new user dedicated to integration use cases with Workato.
CREATE USER 'workato' IDENTIFIED BY 'password';
This allows the user to have login access to the MySQL instance. However, this user will not have access to any tables.
The next step is to grant access to all tables in
HR_PROD. In this example, we only wish to grant
GRANT SELECT ON `HR_PROD`.* TO 'workato';
Finally, check that this user has the necessary permissions. Run a query to see all grants.
SHOW GRANTS FOR 'workato';
This should return the following minimum permission to create a MySQL connection on Workato.
+---------------------------------------------------------------------+ | Grants for workato@% | +---------------------------------------------------------------------+ | GRANT USAGE ON *.* TO 'workato'@'%' IDENTIFIED BY PASSWORD <secret> | | GRANT SELECT ON `HR_PROD`.* TO 'workato'@'%' | +---------------------------------------------------------------------+ 2 rows in set (0.24 sec)
# Working with the MySQL connector
# Table, view and stored procedure
The MySQL connector works with all tables, views and stored procedures. These are available in pick lists in each trigger/action or you can provide the exact name.
Select a table/view from pick list
Provide exact table/view name in a text field
Case sensitivity of the name of a table/view depends on your database implementation. The underlying OS that your database is hosted determines if you need to provide exact table/view names. Typically, database and table names are case insensitive in Windows.
# Single row vs batch of rows
MySQL connector can read or write to your database either as a single row or in batches. When using batch triggers/actions, you have to provide the batch size you wish to work with. The batch size can be any number between 1 and 100, with 100 being the maximum batch size.
Batch trigger inputs
Besides the difference in input fields, there is also a difference between the outputs of these 2 types of operations. A trigger that processes rows one at a time will have an output datatree that allows you to map data from that single row.
Single row output
However, a trigger that processes rows in batches will output them as an array of rows. The Rows datapill indicates that the output is a list containing data for each row in that batch.
Batch trigger output
As a result, the output of batch triggers/actions needs to be handled differently. This recipe uses a batch trigger for new rows in the
users table. The output of the trigger is used in a Salesforce bulk upsert action that requires mapping the Rows datapill into the source list.
Using batch trigger output
# WHERE condition
This input field is used to filter and identify rows to perform an action on. It is used in multiple triggers and actions in the following ways:
- filter rows to be picked up in triggers
- filter rows in Select rows action
- filter rows to be deleted in Delete rows action
This clause will be used as a
WHERE statement in each request. This should follow basic SQL syntax. Refer to this MySQL documentation for a full list of rules for writing MySQL statements.
Greater than |
Greater than or equal to
Less than |
Less than or equal to
|IN(...)||List of values|
|LIKE||Pattern matching with wildcard characters ( |
|BETWEEN||Retrieve values with a range|
IS NULL |
IS NOT NULL
NULL values check |
Non-NULL values check
# Simple statements
String values must be enclosed in single quotes (
'') and columns used must exist in the table.
WHERE condition to filter rows based on values in a single column looks like this.
currency = 'USD'
If used in a Select rows action, this
WHERE condition will return all rows that have the value 'USD' in the
currency column. Just remember to wrap datapills with single quotes in your inputs.
Using datapills in
WHERE statements are for tables and columns identifiers. This is required when the identifier is a MySQL reserved keyword or contains special characters.
`currency` = 'USD'
In a recipe, remember to add backticks to the column identifiers.
Using datapills in
WHERE condition backticks
Double quotes (
"") can also be used for string values but is less commonly accepted in other databases. For this reason, single quotes are used more widely than double quotes.
MySQL also expects
DATETIME values to be single quoted. You can use double quotes for other column types.
created_date > '2018-03-01' and currency = "USD"
In a recipe, remember to use the appropriate quotes for each value.
Using datapills in
WHERE condition with mixed column types
# Complex statements
WHERE condition can also contain subqueries. The following query can be used on the
id in (select user_id from tickets where priority = 2)
When used in a Delete rows action, this will delete all rows in the
users table where at least one associated row in the
tickets table has a value of 2 in the
Using datapills in
WHERE condition with subquery
# Unique key
In all triggers and some actions, this is a required input. Values from this selected column are used to uniquely identify rows in the selected table.
As such, the values in the selected column must be unique. Typically, this column is the primary key of the table (e.g.
When used in a trigger, this column must be incremental. This constraint is required because the trigger uses values from this column to look for new rows. In each poll, the trigger queries for rows with a unique key value greater than the previous greatest value.
Let's use a simple example to illustrate this behavior. We have a New row trigger that processed rows from a table. The unique key configured for this trigger is
ID. The last row processed has
100 as it's
ID value. In the next poll, the trigger will use
ID >= 101 as the condition to look for new rows.
Performance of a trigger can be improved if the column selected to be used as the unique key is indexed.
# Sort column
This is required for New/updated row triggers. Values in this selected column are used to identify updated rows.
When a row is updated, the Unique key value remains the same. However, it should have it's Sort column updated to reflect the last updated time. Following this logic, Workato keeps track of values in this column together with values in the selected Unique key column. When a change in the Sort column value is observed, an updated row event will be recorded and processed by the trigger.
Let's use a simple example to illustrate this behavior. We have a New/updated row trigger that processed rows from a table. The Unique key and Sort column configured for this trigger is
UPDATED_AT respectively. The last row processed by the trigger has
ID value of
UPDATED_AT value of
2018-05-09 16:00:00.000000. In the next poll, the trigger will query for new rows that satisfy either of the 2 conditions:
UPDATED_AT > '2018-05-09 16:00:00.000000'
ID > 100 AND UPDATED_AT = '2018-05-09 16:00:00.000000'
For MySQL, only datetime and timestamp column types can be used.