# JDBC

Connect to any ANSI-compliant database using this connector using a JDBC driver.

# Supported databases

All ANSI-compliant databases with a JDBC driver

# How to connect to JDBC on Workato

To create a connection to a JDBC source, you must use an On-premise agent. The JDBC connector uses JDBC authentication through an On-premise agent to establish a secure connection with your JDBC driver. Learn how to configure an on-premise agent profile to connect to a JDBC-compliant database.

The JDBC connector only supports ANSI-compliant databases like Snowflake and SAP HANA. The database should support binding variables to be able to use some actions such as INSERT.

JDBC connection using on-premise agent

# Working with the JDBC connector

# Table and view

The JDBC connector works with all tables and views available to the credentials used to establish the connection. 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.

# Single row vs batch of rows

JDBC 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. The output of the trigger can be used in actions with batch operations (like Salesforce Create objects in bulk action) that requires mapping the Rows datapill into the source list. Learn how to work with lists in List management.

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.

# Simple statements

String values must be enclosed in single quotes ('') and columns used must exist in the table/view.

A simple 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 has the value 'USD' in the currency column. Just remember to wrap datapills with single quotes in your inputs.

Using datapills in WHERE condition

Column names with spaces must be enclosed in double quotes ("") or square brackets ([]). For example, currency code must to enclosed in brackets to be used as an identifier.

[currency code] = 'USD'

WHERE condition with enclosed identifier

# Complex statements

Your WHERE condition can also contain subqueries. The example below selects inactive employees from the compensation table (presumably to ensure they're not accidentally compensated).

id in (select compensation_id from users where active = 0)

When used in a Select rows action, this will select all rows in the compensation table related to users who are no longer active (active = 0).

Using subquery in WHERE condition