About Mailchimp connector
Etlworks Mailchimp connector allows the fastest and easiest way to connect to real-time Mailchimp data. The connector works just like any other database connector.
Etlworks partnered with CData to provide access to Quickbooks Online using industry-standard JDBC protocol. Read about CData Mailchimp JDBC connector.
When to use Mailchimp connector
Enable the Mailchimp connector for your Etlworks Integrator account. Contact
firstname.lastname@example.org to enable the connector.
Create a Connection
You can create a Connection in just two steps, and they are the following:
Step 1. In the
Connections window, click
+, and type in
Step 2. Enter the Connection parameters:
OAuth Scopes: select authentication type, either OAuth (default) or API Key.
When using OAuth authentication (default):
Sign in with Mailchimp.
When using API Key authentication:
API Key: the API key. Read about Mailchimp API keys.
Other Parameters to specify the Connection string options. Read about available Connection string options.
Work with Mailchimp
Mailchimp Data Model
The Data Model has three parts: Tables, Views, and Stored Procedures. API limitations and requirements are documented in this section; you can use the
SupportEnhancedSQL feature, set by default to circumvent most of these limitations.
Read about the data model.
Stored procedures are available to complement the data available from the Data Model. It may be necessary to update data available from a view using a stored procedure because the data does not provide for direct, table-like, two-way updates. In these situations, the data retrieval is done using the appropriate view or table, while the update is done by calling a stored procedure. Stored procedures take a list of parameters and return a dataset that contains the collection of tuples that constitute the response.
Read about available stored procedures in the data model.
To call stored procure from the SQL Flow or Before/After SQL, use
EXEC sp_name params=value.
EXECUTE my_proc @second = 2, @first = 1, @third = 3;
The connector supports several operations on data, including querying, deleting, modifying, and inserting.
Read about SQL Compliance.
Extract data from Mailchimp
Extracting data from Mailchimp is similar to extracting data from the relational database.
Here are the steps on how you can extract data from Mailchimp:
Step 1. Create Mailchimp Connection which will be used as a source (
Step 3. Create a Flow where the
source is a database and the destination is a Connection created in step 2, for example, a relational database.
Step 4. Add a new source-to-destination transformation.
Step 5. Select the Mailchimp Connection created in step 1 as a source Connection and select the data object you are extracting data from.
Step 6. Select
TO Connection, Format (if needed), and object (for example, database table) to load data into.
Step 7. Click
MAPPING and optionally enter
Source query (you don't need a query if you are extracting data from the Mailchimp data object unconditionally).
Step 8. Optionally define the per-field Mapping.
Step 9. Add more transformations if needed.
Load data in Mailchimp
Loading data in Mailchimp is similar to loading data into a relational database.
Here are the steps on how you can load data in Mailchimp:
Step 1. Create a source Connection and a Format (if needed).
Step 2. Create a destination Mailchimp Connection.
Step 3. Create a Flow where the destination is a database.
Step 4. Add new source-to-destination transformation.
Step 5. Select
TO Connections and objects (also a
FROM Format if needed).
Step 6. Optionally define the per-field Mapping.
Step 7. Add more transformations if needed.
Browse data in Mailchimp
You must have Mailchimp Connection to browse objects and run SQL queries.
Use the Etlworks Explorer to browse data and metadata in Mailchimp as well as execute
SELECT queries against the Mailchimp Connection.