- This component is only available for use with Hybrid SaaS agents.
- When adding new drivers, an agent restart is required to recognize the configuration. Once the agent has restarted, you can choose the driver from the Database Type property in the component.
- For connecting to Oracle Autonomous Databases, read the Oracle Autonomous Database authentication guide.
Storage Blob Data Contributor role. For more information, read User assigned with the Storage Blob Data Contributor role.
For Snowflake projects, this component supersedes the JDBC component, which is no longer available for new pipelines.Existing pipelines with the JDBC component will continue to work as expected.
Properties
Reference material is provided below for the Connect, Configure, Destination, and Advanced Settings properties.Connect
Select the database type. The drop-down will contain all databases that you have included in the manifest file.
The URL for your chosen JDBC database. If the field displays a template URL for the database, replace any placeholder values with the actual values of your database’s URL.Although many parameters and options can be added to the end of the URL, it’s generally easier to add them in the Connection Options property, documented below.
Currently only supports Username & Password or None.
Your username for the JDBC data source.
Displays a drop-down list of secret definitions. Select the secret definition that references the password corresponding to the username.
- Parameter: A JDBC parameter supported by the database driver. The available parameters are explained in the data model. Manual setup is not usually required, since sensible defaults are assumed.
- Value: A value for the given parameter.
Configure
- Full Load: Select this option to load your entire dataset.
- Incremental Load: Select this option to only load new and updated records from your dataset.
- Basic: This mode will build a query for you using settings from the Schema, Data Source, Data Selection, Data Source Filter, Combine Filters, and Limit parameters. In most cases, this mode will be sufficient.
- Advanced: This mode will require you to write an SQL-like query to call data from the service you’re connecting to. The available fields and their descriptions are documented in the data model.
Advanced mode is currently not supported when Incremental Load is selected.
While the query is exposed in an SQL-like language, the exact semantics can be surprising, for example, filtering on a column can return more data than not filtering on it. This is an impossible scenario with regular SQL.
This is an SQL-like SELECT query. Treat collections as table names, and fields as columns. Only available in Advanced mode.For more information, read the Snowflake SELECT documentation.
Select the database schema to load data from.
Select a single data source to be extracted from the source system and loaded into a table in the destination. The source system defines the data sources available. Use multiple components to load multiple data sources.
Choose one or more columns to return from the query. The columns available are dependent upon the data source selected. Move columns left-to-right to include in the query.To use grid variables, select the Use Grid Variable checkbox at the bottom of the Data Selection dialog.
Define one or more filter conditions that each row of data must meet to be included in the load.
- Input Column: Select an input column. The available input columns vary depending upon the data source.
- Qualifier: Is compares the column to the value using the comparator. Not reverses the effect of the comparison, so “Equals” becomes “Not equals”, “Less than” becomes “Greater than or equal to”, etc.
- Comparator: Choose a method of comparing the column to the value. Possible comparators include: “Equal to”, “Greater than”, “Less than”, “Greater than or equal to”, “Less than or equal to”, “Like”, “Null”. Not all data sources support all comparators.
- Value: The value to be compared.
The data source filters you have defined can be combined using either And or Or logic. If And, then all filter conditions must be satisfied to load the data row. If Or, then only a single filter condition must be satisfied. The default is And.If you have only one filter, or no filters, this parameter is essentially ignored.
Set a numeric value to limit the number of rows that are loaded. The default is an empty field, which will load all rows.
When Incremental Load is selected, select a datetime field from your dataset that is always updated when your data changes, such as
dateModified. The connector will record the maximum value of this field each time you run this pipeline. On subsequent runs when Incremental Load is selected, only data with a higher value in this field will be loaded.If no rows in the source have a higher value than the stored high-water mark, the task will complete with a “task is skipped” message. This is expected behavior, indicating that no new or updated data was found since the last successful run.
Destination
- Snowflake
Select the destination for your data. This is either in Snowflake as a table or as files in cloud storage.
- Snowflake: Load your data into a table in Snowflake. The data must first be staged via Snowflake or a cloud storage solution.
- Cloud Storage: Load your data directly into files in your preferred cloud storage location. The format of these files can differ between source systems and will not have a file extension so we suggest inspecting the output to determine the format of the data.
- Snowflake
- Cloud Storage
The Snowflake warehouse used to run the queries. The special value
[Environment Default] uses the warehouse defined in the environment. Read Overview of Warehouses to learn more.The Snowflake database to access. The special value
[Environment Default] uses the database defined in the environment. Read Databases, Tables and Views - Overview to learn more.The Snowflake schema. The special value
[Environment Default] uses the schema defined in the environment. Read Database, Schema, and Share DDL to learn more.The name of the table to be created in your Snowflake database. You can use a Table Input component in a transformation pipeline to access and transform this data after it has been loaded.
Define what happens if the table name already exists in the specified Snowflake database and schema. Only available when Full Load is selected.
- Replace: If the specified table name already exists, that table will be destroyed and replaced by the table created during this pipeline run.
- Truncate and Insert: If the specified table name already exists, all rows within the table will be removed and new rows will be inserted per the next run of this pipeline.
- Fail if Exists: If the specified table name already exists, this pipeline will fail to run.
- Append: If the specified table name already exists, then the data is inserted without altering or deleting the existing data in the table. It’s appended onto the end of the existing data in the table. If the specified table name doesn’t exist, then the table will be created, and your data will be inserted into the table.
Choose one or more columns to be designated as the table’s primary key.When Incremental Load is selected, if a primary key is selected, the loaded data will be merged with your existing data. If no primary key is selected, the loaded data will be appended to your existing data.
- Yes: Staged files will be destroyed after data is loaded. This is the default setting.
- No: Staged files are retained in the staging area after data is loaded.
Select the stage access strategy. The strategies available depend on the cloud platform you select in Stage Platform.
- Credentials: Connects to the external stage (AWS, Azure) using your configured cloud provider credentials. Not available for Google Cloud Storage.
- Storage Integration: Use a Snowflake storage integration to grant access to Snowflake to read data from and write to a cloud storage location. This will reveal the Storage Integration property, through which you can select any of your existing Snowflake storage integrations.
Use the drop-down menu to choose where the data is staged before being loaded into your Snowflake table.
- Amazon S3: Stage your data on an AWS S3 bucket.
- Snowflake: Stage your data on a Snowflake internal stage.
- Azure Storage: Stage your data in an Azure Blob Storage container.
- Google Cloud Storage: Stage your data in a Google Cloud Storage bucket.
Advanced Settings
Converts common strings that represent null into a null value. This is case-sensitive and works with the following strings: "", “NULL”, “NUL”, “Null”, “null”. The default is No.
Currently, this property is only applicable when using Snowflake as your destination.
When Yes, remove leading and trailing characters from a string column. The default is No.
Manifest file
The manifest file is a JSON format text file that includes the configuration information needed to connect to the data source. Every data source that you upload an external driver for must have a corresponding entry in the manifest file. The manifest file must be namedjdbc-driver-manifest.json and saved to the storage location that also holds the uploaded external driver files.
A manifest file must be in valid JSON format and strictly follow this structure:
< > above with the actual values required by the driver you are using, in accordance with the following notes:
-
name: This should be a simple name for the driver that identifies the database type it’s used with. For example
MySQL,Mailchimp, orPostgreSQL. The name will appear in the component’s Database Type drop-down. -
driverClassName: The fully qualified name of a class that implements the
java.sql.Driverinterface in Java. The fully qualified name of the driver class includes the package name followed by the class name, ensuring it’s unique across all Java packages. For example, the driver class name for MySQL’s Connector/J driver iscom.mysql.cj.jdbc.Driver(version 8.0 and above), and the class name for the PostgreSQL driver isorg.postgresql.Driver. -
baseUrl: A template URL used to prompt the user to enter the correct format of URL in the component’s Connection URL property. This should be the basic URL for the driver, such as
jdbc:postgresql://orjdbc:cdata:mailchimp:. -
limitStrategy: Controls how the component gets metadata about the query. Different databases have different ways of supporting this. Enter the method required by the data source you are configuring:
limit-inline: The most straightforward and widely supported method for limiting query results, commonly used in MySQL, PostgreSQL, SQLite, and others.top-n: Similar tolimit-inline, but commonly used in SQL Server and Sybase.fetch-first-n: Similar tolimit-inline, but supported by newer versions of databases such as DB2, Oracle (12c and later), and PostgreSQL.rownum: Uses a pseudocolumn in Oracle to limit the number of rows returned, and is particularly useful for complex queries or pagination.limit-outer: A sophisticated technique to limit query results by wrapping the main query within an outer query where the limit is applied. This strategy is particularly useful for complex queries that require pre-processing steps before the application of the limit. Commonly used in databases that can use optimized nested queries.none: No limit is applied to the query, either due to retrieving all records for processing or when the dataset is known to be within acceptable size limits. Commonly used in all SQL databases.
-
fetchSize: Used in conjunction with the limitStrategy, this is the number of rows fetched at once, if supported by the database driver. Enter this as a JSON integer value, i.e. not within
" ". -
defaultProperties: Define any required defaults for driver properties. These defaults can be overridden by the user when the component is configured (but see blacklistedProperties, below, for how to prevent overrides).
List the name of each default property and its default value as a name:value pair inside the
defaultPropertiesobject. This is a JSON object requiring{ }delimiters. For example:If there are no default properties, this element is still required and should be an empty object: -
blacklistedProperties: List any properties that you don’t want to be accessible from the UI. For example, if you have set a default property here in the manifest file that you don’t want the pipeline creator to be able to override in the UI, you should list it here.
List the name of each blacklisted property inside the
blacklistedPropertiesarray. This is a JSON array requiring[ ]delimiters. For example:If there are no blacklisted properties, this element is still required and should be an empty array: -
propertyOverrides: If the driver is expecting property names that are different from those used by the component, you can map the expected names here. For example, MySQL expects “user” instead of “username” as used by the component, so in a manifest file for MySQL you would specify:
"username": "user". List each required override inside thepropertyOverridesobject. This is a JSON object requiring{ }delimiters. For example:If there are no required overrides, this element is still required and should be an empty object: -
skipQueryValidation: The component’s default behavior is to validate a query written in Advanced mode by fetching metadata from the data source. In some cases, returning metadata takes a considerable time, resulting in slow validation of the component. To avoid such delays, include this property in your manifest file and set it to
true. This property is optional, and should be omitted if not needed.

