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Redshift

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IBM DB2

Execute a prepared statement with multiple sets of parameters. This operation can only be used for updating information in a database; it does not accept SELECT statements.

Batch execute prepared statement

Execute multiple raw statements in the same database call. This operation can only be used for updating information in a database; it does not accept SELECT statements.

Batch execute raw statements

Execute query

Execute an update statement (i.e., a statement that does not return any data).

Execute update

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Learn How to Automate Your CSV and Flat File Management

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Java Database Connectivity (JDBC)

Database

Duplicate Column

Delete Rows

Update a single column in multiple rows using a function

Update by Function

Delete Row

Create a temporary CSV for use within the current workflow execution from an existing file. You can perform operations on this CSV within a single workflow execution, but will need to export the CSV at the end otherwise it will be deleted.

Create CSV From File

Parse Text

Rename Column

Rename Columns

Sort CSV

Add Column

Change the characters (such as delimiter and escape character) used in a CSV. This operation may be required for CSVs with embedded new lines and quote character in cell values.

Format CSV

Add Row

Create a temporary CSV for use within the current workflow execution from an existing XLSX file. You can perform operations on this CSV within a single workflow execution, but will need to export the CSV at the end otherwise it will be deleted.

Create CSV From XLSX File

Create a temporary CSV for use within the current workflow execution from an existing XML file. You can perform operations on this CSV within a single workflow execution, but will need to export the CSV at the end otherwise it will be deleted.

Create CSV From XML File

Delete all rows that match a specific filter.

Delete Rows By Filter

Delete a specific CSV created in Current Run and Account scope.

Delete a CSV

Delete column

Delete columns

Export an in memory CSV into a file for persistence and use elsewhere.

Export CSV

Export an in memory CSV data into a plain text file using a template configuration

Export File

Export an in memory CSV into a JSON file for persistence and use elsewhere.

Export JSON

Find the first row in the table that matches a specific filter.

Find Row

Find rows in the table that match a specific filter.

Find Rows By Filter

Generate a list of column descriptions from a JSON object (ignoring nested arrays and objects), and provide optional column type definitions to change the types of some fields.

Generate columns from object

Return the data in a specifc cell in the CSV.

Get Cell

Return the number of columns that are available in an in memory CSV.

Get Column Count

Return all columns from single row in the CSV.

Get Row

Return the number of rows that are available in an in memory CSV.  This doesn't take into account content.

Get Row Count

Return all columns from a number of rows from in the CSV.

Get Rows

Return a single column from a number of rows from in the CSV.

Get column from rows

Import an external CSV file into an existing in memory CSV

Import Data

Set new values in all rows matching given filters, in the CSV

Update Rows by Filter

Add Rows

Duplicate

Update Cell

Create a temporary CSV for use within the current workflow execution.  You can perform operations on this CSV within a single workflow execution, but will need to export the CSV at the end otherwise it will be deleted.

Create CSV

Join two CSVs together based on a common field, using a left, inner or outer join. Indexes will automatically be created on for the columns chosen.

Join CSVs

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Integration

Integrate your CSVs with any data source, fast

CSV 2

Automation

Powerful CSV automation

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Use cases

Take full control of your CSV data

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Similar connectors to Java Database Connectivity (JDBC) and CSV

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Java Database Connectivity (JDBC) and CSV integrations couldn’t be easier with the Tray platform’s robust Java Database Connectivity (JDBC) and CSV connector, which connects any services without the need for separate integration tools.

Java Database Connectivity (JDBC) and CSV integrations couldn’t be easier with the Tray platform’s robust Java Database Connectivity (JDBC) and CSV connectors, which can connect to any service without the need for separate integration tools.

Integrate Java Database Connectivity (JDBC) and CSV with any SaaS application or service using the Tray platform’s generic connectivity options, such as the HTTP Client, Webhook Trigger, and our Connector Builder. Configure them to connect to Java Database Connectivity (JDBC) and CSV and any other API, database, webhook, and more.

Java Database Connectivity (JDBC) and CSV integration + automation

Java Database Connectivity (JDBC) and CSV Connector Details

Popular Java Database Connectivity (JDBC) and CSV integrations

Java Database Connectivity (JDBC) and CSV templates