About Azure Table connector
Etlworks Azure Table connector allows the fastest and easiest way to connect to Azure Table storage data. The connector works just like any other database connector.
Etlworks partnered with CData to provide access to Azure Table storage using industry-standard JDBC protocol. Read about CData Azure Table JDBC connector.
When to use Azure Table connector
Enable the Azure Table connector for your Etlworks Integrator account. Contact
email@example.com 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:
Account: enter the storage account name.
Access Key: enter the access key for the account.
Read about Authentication with an Access key.
Other Parameters to specify the Connection string options. Read about available Connection string options.
Work with Azure Table
Azure Table Data Models
Azure tables are highly scalable NoSQL cloud databases that are very different from a regular database.
Read about the Azure Table 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 Azure Table
Extracting data from Azure Table is similar to extracting data from the relational database.
Here are the steps on how you can extract data from Azure Table:
Step 1. Create Azure Table 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 Azure Table 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 Azure Table data object unconditionally).
Step 8. Optionally define the per-field Mapping.
Step 9. Add more transformations if needed.
Load data in Azure Table
Loading data in Azure Table is similar to loading data into a relational database.
Here are the steps on how you can load data in Azure Table:
Step 1. Create a source Connection and a Format (if needed).
Step 2. Create a destination Azure Table 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 Azure Table
You must have an Azure Table Connection to browse objects and run SQL queries.
Use the Etlworks Explorer to browse data and metadata in Azure Table as well as execute
SELECT queries against the Azure Table Connection.