Shopify Connector for Azure Data Factory (Pipeline) In this article you will learn how to integrate Shopify data in Azure Data Factory (Pipeline) without coding in just a few clicks (live / bi-directional connection to Shopify). Shopify Connector can be used to integrate Shopify REST API in your App / BI Tools. You can read/write data about Customers, Orders, OrderItems, Products and more.. Using Shopify Connector you will be able to connect, read, and write data from within Azure Data Factory (Pipeline). Follow the steps below to see how we would accomplish that. Download Documentation The driver mentioned above is part of ODBC PowerPack which is a collection of high-performance Drivers for various API data source (i.e. REST API, JSON, XML, CSV, Amazon S3 and many more). Using familiar SQL query language you can make live connections and read/write data from API sources or JSON / XML / CSV Files inside SQL Server (T-SQL) or your favorite Reporting (i.e. Power BI, Tableau, Qlik, SSRS, MicroStrategy, Excel, MS Access), ETL Tools (i.e. Informatica, Talend, Pentaho, SSIS). You can also call our drivers from programming languages such as JAVA, C#, Python, PowerShell etc. If you are new to ODBC and ZappySys ODBC PowerPack then check the following links to get started. ODBC PowerPack - System Requirements and Installation Getting Started - Using ODBC PowerPack ODBC API Driver Help File

Connect to Shopify in other apps Connect to Shopify in SSIS Connect to Shopify in SQL Server Connect to Shopify in Power BI Connect to Shopify in SSRS Connect to Shopify in Informatica Connect to Shopify in MS Access Connect to Shopify in MS Excel Connect to Shopify in SSAS Connect to Shopify in C# Connect to Shopify in Python Connect to Shopify in JAVA Connect to Shopify in Tableau Connect to Shopify in SAP Crystal Reports Connect to Shopify in Azure Data Factory (SSIS) Connect to Shopify in Talend Studio Connect to Shopify in UiPath Connect to Shopify in PowerShell Connect to Shopify in ODBC

Create ODBC Data Source (DSN) based on ZappySys API Driver

Step-by-step instructions

To get data from Shopify using Azure Data Factory (Pipeline) we first need to create a DSN (Data Source) which will access data from Shopify. We will later be able to read data using Azure Data Factory (Pipeline). Perform these steps:

1. Install ZappySys ODBC PowerPack.

2. Open ODBC Data Sources (x64):
   

3. Create a System Data Source (System DSN) based on ZappySys API Driver

   ZappySys API Driver

   
   You should create a System DSN (instead of a User DSN) if the client application is launched under a Windows System Account, e.g. as a Windows Service. If the client application is 32-bit (x86) running with a System DSN, use ODBC Data Sources (32-bit) instead of the 64-bit version. Furthermore, a User DSN may be created instead, but then you will not be able to use the connection from Windows Services(or any application running under a Windows System Account).

4. When the Configuration window appears give your data source a name if you haven't done that already, then select "Shopify" from the list of Popular Connectors. If "Shopify" is not present in the list, then click "Search Online" and download it. Then set the path to the location where you downloaded it. Finally, click Continue >> to proceed with configuring the DSN:

   ShopifyDSN

   Shopify

   

5. Now it's time to configure the Connection Manager. Select Authentication Type, e.g. Token Authentication. Then select API Base URL (in most cases, the default one is the right one). More info is available in the Authentication section.

    Access Token [Http]

   Steps to get Shopify Credentials : Access Token [Http]
   Setting up your Shopify store account for API access involves creating an "app" for your store. The "app" is installed into the Shopify account and configured with the appropriate access levels for your data integration needs.

   1. Visit https://accounts.shopify.com and log into your Shopify store account.
   2. After logging in, select the store to connect to with the ZappySys Shopify Connector.
   3. Select the Settings link (usually in the lower-left corner) to launch the Settings screen.
   4. On the left menu panel, select Apps and sales channels.
   5. On the Apps and sales channels screen, select Develop apps (near the top of the screen).
   6. On the App development screen, select Create an app (near the upper-right corner of the screen).
   7. Give the app that will be used to provide Shopify API access a name, select the appropriate developer from the App developer drop-down, and then select Create app.
   8. Select Configure Admin API scopes and the Admin API access scopes screen will appear.
   9. In the Admin API access scopes screen, select every access scope checkbox that applies to your integration needs. It is generally not a good idea to allow more access than what is needed in order to fulfill your integration needs.
      • To enable the reading of customer information, select read_customers.
      • To enable the writing of customer information, select write_customers.
      • To enable the reading of inventory item information, select read_inventory.
      • To enable the writing of inventory item information, select write_inventory.
      • To enable the reading of order information, select read_orders.
      • To enable the writing of order information, select write_orders.
      After selecting all applicable access scopes, select Save.
   10. Install the app by selecting the Install app button (near the upper-right corner of the screen). If any other prompts for installation appears, select Install.
   11. After the app is installed, the Admin API access token will be available in the API credentials tab of the page. It can only be revealed ONCE for security purposes. Select Reveal token once to show the new Admin API access token. SAVE THE ADMIN API ACCESS TOKEN IN A SAFE PLACE WHERE YOU HAVE IT CONFIDENTIAL, SECURE, AND NOT ACCESSIBLE TO UNAUTHORIZED INDIVIDUALS. The Admin API access token will be needed in this process later.
   12. In the ZappySys connector API screen, enter the subdomain of your Shopify store into the Subdomain parameter textbox. For example, if your Shopify URL is https://acmetoys.myshopify.com, the subdomain would be acmetoys.
   13. In the same screen, enter the Admin API access token saved from step 11 above into the Admin API Access Token textbox. In order to edit the text in this field, select the ellipses (...) button that appears when the textbox is clicked and edit the access token with the dialog box that appears.
   14. Select the Test Connection button at the bottom of the window to verify proper connectivity with the Shopify store.
   15. If the connection test succeeds, select OK.

   Fill in all required parameters and set optional parameters if needed:

   ShopifyDSN

   Shopify

   Access Token [Http]

   https://[$Subdomain$].myshopify.com/admin/api/2023-01

   Required Parameters
   Sub-domain	Fill in the parameter...
   Admin API Access Token	Fill in the parameter...
   Optional Parameters
   RetryMode	Fill in the parameter...
   RetryStatusCodeList	Fill in the parameter...
   RetryCountMax	Fill in the parameter...
   RetryMultiplyWaitTime	Fill in the parameter...

   

6. Once the data source has been configured, you can preview data. Select the Preview tab and use settings similar to the following to preview data:
   

7. Click OK to finish creating the data source.

Video instructions

Read data in Azure Data Factory (ADF) from ODBC datasource (Shopify)

1. To start press New button:

   

2. Select "Azure, Self-Hosted" option:

   

3. Select "Self-Hosted" option:

   

4. Set a name, we will use "OnPremisesRuntime":

   

5. Download and install Microsoft Integration Runtime.

6. Launch Integration Runtime and copy/paste Authentication Key from Integration Runtime configuration in Azure Portal:

   

7. After finishing registering the Integration Runtime node, you should see a similar view:

   

8. Go back to Azure Portal and finish adding new Integration Runtime. You should see it was successfully added:

   

9. Go to Linked services section and create a new Linked service based on ODBC:

   

10. Select "ODBC" service:

    

11. Configure new ODBC service. Use the same DSN name we used in the previous step and copy it to Connection string box:

    ShopifyDSN

    DSN=ShopifyDSN

    

12. For created ODBC service create ODBC-based dataset:

    

13. Go to your pipeline and add Copy data connector into the flow. In Source section use OdbcDataset we created as a source dataset:

    

14. Then go to Sink section and select a destination/sink dataset. In this example we use precreated AzureBlobStorageDataset which saves data into an Azure Blob:

    

15. Finally, run the pipeline and see data being transferred from OdbcDataset to your destination dataset:

    

Advanced topics

Create Custom Stored Procedure in ZappySys Driver

You can create procedures to encapsulate custom logic and then only pass handful parameters rather than long SQL to execute your API call.

Steps to create Custom Stored Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here

1. Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
   

2. Enter the desired Procedure name and click on OK:
   

3. Select the created Stored Procedure and write the your desired stored procedure and Save it and it will create the custom stored procedure in the ZappySys Driver:
   Here is an example stored procedure for ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
   

   CREATE PROCEDURE [usp_get_orders]
       @fromdate = '<<yyyy-MM-dd,FUN_TODAY>>'
    AS
       SELECT * FROM Orders where OrderDate >= '<@fromdate>';
   

   
   

4. That's it now go to Preview Tab and Execute your Stored Procedure using Exec Command. In this example it will extract the orders from the date 1996-01-01:
   

   Exec usp_get_orders '1996-01-01';

   
   

5. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC usp_get_orders @fromdate=''1996-07-30''')

   
   

6. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Create Custom Virtual Table in ZappySys Driver

ZappySys API Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

If you're dealing with Microsoft Access and need to import data from an SQL query, it's important to note that Access doesn't allow direct import of SQL queries. Instead, you can create custom objects (Virtual Tables) to handle the import process.

Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 URLs with slight variations you can create virtual tables with just URL as Parameter setting.

1. Go to Custom Objects Tab and Click on Add button and Select Add Table:
   

2. Enter the desired Table name and click on OK:
   

3. And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.

4. Select the created table, Select Text Type AS SQL and write the your desired SQL Query and Save it and it will create the custom table in the ZappySys Driver:
   Here is an example SQL query for ZappySys Driver. You can insert Placeholders also. Read more about placeholders here
   

   SELECT
     "ShipCountry",
     "OrderID",
     "CustomerID",
     "EmployeeID",
     "OrderDate",
     "RequiredDate",
     "ShippedDate",
     "ShipVia",
     "Freight",
     "ShipName",
     "ShipAddress",
     "ShipCity",
     "ShipRegion",
     "ShipPostalCode"
   FROM "Orders"
   Where "ShipCountry"='USA'

   
   

5. That's it now go to Preview Tab and Execute your custom virtual table query. In this example it will extract the orders for the USA Shipping Country only:
   

   SELECT * FROM "vt__usa_orders_only"

   
   

6. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC [usp_get_orders] ''1996-01-01''')

   
   

7. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Actions supported by Shopify Connector

Shopify Connector Examples for Azure Data Factory (Pipeline) Connection

This page offers a collection of SQL examples designed for seamless integration with the ZappySys API ODBC Driver under ODBC Data Source (36/64) or ZappySys Data Gateway, enhancing your ability to connect and interact with Prebuilt Connectors effectively.

SELECT * FROM Products

SELECT * FROM Products WITH Id=1111111111111

SELECT * FROM Products WITH(ids='1111111111111,2222222222222,3333333333333')

INSERT INTO Products 
(
	 Title
	,Status
	,BodyHtml
	,UrlHandle
	,Vendor
	,ProductType
	,Variants
	,Options
	,Tags
	,Metafields
	,Images	
	)
VALUES	
('Ice Cream'
,'draft'
,'<strong>Very yummy ice cream!</strong>'
,'ice-cream' 
,'Burton'
,'Snowboard' 

,'[
	{"price":10.5, "option1":"Chocolate","option2":"Small","sku":"ICE-CHO-SML","inventory_quantity":100},
	{"price":10.5, "option1":"Chocolate","option2":"Medium","sku":"ICE-CHO-MED","inventory_quantity":100},
	{"price":11.5, "option1":"Vanilla","option2":"Small","sku":"ICE-VNL-MED","inventory_quantity":210}
  ]'

--you must set variants and use atlease one value from the below list in option1, option2 or option3 in any variant entry else it will fail.  
,'[
	{"name":"Color","values":["Chocolate","Vanilla"]}, 
	{"name":"Size","values":["Small","Medium"]}
  ]' 

,'["Frozen","Seasonal","Dad''s Fav"]'

--adding metadata (custom fields) - metadata fields must be created before setting it 
--below are 2 system fields for SEO Title / SEO Description (you dont need to create them unlike custom metadata). These values appears on SEO section
,'[
	{"key":"title_tag","value":"Yum Ice Cream SEO Title", "namespace":"global","type":"single_line_text_field"}, 
	{"key":"description_tag","value":"Yum Ice Cream SEO description", "namespace":"global","type":"single_line_text_field"} 
  ]'

--first image becomes main image if you supply multiple images 
--upload multiple images from URL (set "src")
 , '[	
	{"src":"https://zappysys.com/images/tech/google-analytics-logo.png"},
	{"src":"https://zappysys.com/images/tech/web-api-logo.png"}
  ]'
--OR upload multiple local image files (set "attachment")
--, '[	
--	 {"attachment":"<<c:\temp\icecream_1.png,FUN_FILE_BASE64ENC>>"},
--	 {"attachment":"<<c:\temp\icecream_2.png,FUN_FILE_BASE64ENC>>"}
--  ]'  
  
)

UPDATE Products
SET Title='Ice Cream - Updated'
 , Status='draft' --active, archived, draft  
 , BodyHtml='<strong>Very yummy ice cream - updated!</strong>'  
--first image becomes main image if you supply multiple images 
--upload multiple images from URL (set "src")
 , Images='[	
	{"src":"https://zappysys.com/images/tech/google-analytics-logo.png"},
	{"src":"https://zappysys.com/images/tech/web-api-logo.png"}
  ]'
--OR upload multiple local image files (set "attachment")
--, Images='[	
--	 {"attachment":"<<c:\temp\icecream_1.png,FUN_FILE_BASE64ENC>>"},
--	 {"attachment":"<<c:\temp\icecream_2.png,FUN_FILE_BASE64ENC>>"}
--  ]'

 , Variants='[
	{"price":20.5, "option1":"Chocolate","option2":"Small","sku":"ICE-CHO-SML","inventory_quantity":300},
	{"price":21.5, "option1":"Vanilla","option2":"Small","sku":"ICE-VNL-MED","inventory_quantity":110}
  ]'
, PublishedScope='global' --or web
, Vendor ='IceGlobal'
, ProductType ='Cold Food'
, Tags ='["Frozen","Seasonal","Dad''s Fav"]'
--Update SEO URL
 ,UrlHandle='ice-cream-51' 
--Update SEO title / description
, SEOTitle='Yum Ice Cream SEO Title-update'  
, SEODescription='Yum Ice Cream SEO description-update'  
Where Id=7348335771748

DELETE FROM Products
Where Id=7348335771748

SELECT * FROM ProductVariants

SELECT * FROM ProductVariants Where ProductId='1111111111111'

SELECT * FROM ProductVariants WITH(ids='1111111111111,2222222222222,3333333333333')

INSERT INTO ProductVariants (ProductId, Option1, Option2,SKU,Price,CompareAtPrice,Position,Weight,WeightUnit,ImageId)
Values(7348335771748, 'Chocolate', 'Medium', 'ICE-CHO-MED', 195.5, 200.5, 3, 20.5, 'lb', 31900013854820)

Update ProductVariants 
SET  
	,Option1='Chocolate' 
	,Option2='Large'
	,SKU='ICE-CHO-SML'
	,Price=90.45
	,CompareAtPrice=100.45
	,Position=2
	,Weight=10.5
	,WeightUnit='lb'
	,ImageId=31900013854820  --use available images from Products table
Where Id=42564507992164

DELETE FROM ProductVariants 
WHERE Id=31900013854820

SELECT * FROM Customers

SELECT * FROM Customers Where Id=12345

SELECT * FROM Customers
WITH (ids='1111111111111,2222222222222,3333333333333')

INSERT INTO Customers
(FirstName, LastName, Email, Phone, Password, PasswordConfirmation, SendWelcomeEmail, MultipassIdentifier, Note, Tags, TaxExempt, TaxExemptions, DefaultAddressFirstName, DefaultAddressLastName, DefaultAddressCompany, DefaultAddressLine1, DefaultAddressLine2, DefaultAddressCity, DefaultAddressProvince, DefaultAddressCountry, DefaultAddressZip, DefaultAddressPhone, DefaultAddressName, DefaultAddressProvinceCode, DefaultAddressCountryCode, DefaultAddressCountryName)
VALUES
('John', 'Doe', 'john.doe@gmail.com', '7705553543', 'myNewP@ssword123', 'myNewP@ssword123', 1, null, 'This is a note on the customer account.', null, 0, null, 'John', 'Doe', 'John Doe Corp.', '123 Main Street', null, 'Atlanta', 'Georgia', 'United States', '30135', '7705553543', 'John Doe', 'GA', 'US', 'United States')

INSERT INTO Customers(_rawdoc_)
VALUES('{"customer":{"first_name":"John","last_name":"Doe","email":"a.doe@gmail.com","phone":"7705553111"}}')

INSERT INTO Customers(FirstName, LastName, Email, Phone)
SOURCE('MSSQL'
  ,'Data Source=localhost;Initial Catalog=tempdb;Integrated Security=true'
  ,'select ''John'' as FirstName, ''Doe'' as LastName, ''a.doe@gmail.com'' as Email, ''7705553111'' as Phone'
)

INSERT INTO Customers
SOURCE('MSSQL'
	,'Data Source=localhost;Initial Catalog=tempdb;Integrated Security=true'
	,'select ''{"customer":{"first_name":"Cust1","last_name":"Doe1","email":"a.doe@gmail.com","phone":"7705553111"}}'' as _rawdoc_
	 UNION 
	 select ''{"customer":{"first_name":"Cust2","last_name":"Doe2","email":"b.doe@gmail.com","phone":"7705553222"}}'' as _rawdoc_
	 '
	)

UPDATE Customers SET
  Email = 'john.doe2@gmail.com',
  Phone = '7705553445',
  Note= 'This is a new note that needed to be added later.'
  WHERE Id=1111111111111

UPDATE Customers
SET _rawdoc_='{"customer":{"first_name":"John_new","last_name":"Doe_new","email":"a_new.doe@gmail.com","phone":"7705553111"}}'
WHERE Id=1111111111111

UPDATE Orders SET
  FulfillmentStatus = 'john.doe5@gmail.com',
  Phone = '7705553111',
  Note= 'This is a new note that needed to be added to the order later.'
WHERE Id=1111111111111

UPDATE Customers
SOURCE('MSSQL'
 ,'Data Source=localhost;Initial Catalog=tempdb;Integrated Security=true'
 ,'select 111 as Id, ''a@a.com''Email , ''SOLD'' as Note,0 as [$$ContineOn404Error]
  UNION
  select 222 as Id, ''b@b.com''Email , ''SOLD'' as Note,0 as [$$ContineOn404Error]
  '
)

DELETE Customers WHERE Id=1111111111111

DELETE Customers WHERE Id=1111111111111 (ContineOn404Error=0)

DELETE FROM Customers
SOURCE('MSSQL'
  ,'Data Source=localhost;Initial Catalog=tempdb;Integrated Security=true'
  ,'select 111 as Id,1 as [$$ContineOn404Error]
    UNION
    select 222 as Id,1 as [$$ContineOn404Error]
   '
)

SELECT * FROM Orders

SELECT * FROM Orders WITH (Status='open') --also try 'any', 'open', 'closed', 'cancelled'

SELECT * FROM Orders Where Id=1111111111111

SELECT * FROM Orders WITH(ids='1111111111111,2222222222222,3333333333333')

DELETE Orders WHERE Id=1111111111111

DELETE Orders WHERE Id=1111111111111 (ContineOn404Error=0)

SELECT * FROM OrderItems

SELECT * FROM OrderItems Where OrderId=1111111111111

SELECT * FROM OrderItems WITH(ids='1111111111111,2222222222222,3333333333333')

INSERT INTO Orders (BillingAddressLine1, BillingAddressLine2, BillingAddressCity, BillingAddressCompany, BillingAddressCountry, BillingAddressFirstName, BillingAddressLastName, BillingAddressPhone, BillingAddressProvince, BillingAddressZip, BillingAddressName, BillingAddressProvinceCode, BillingAddressCountryCode, BuyerAcceptsMarketing, LineItems, CustomerId, Email, EstimatedTaxes, FinancialStatus, FulfillmentStatus, Name, Note, Phone, Currency, PresentmentCurrency, ProcessedAt, ReferringSite, ShippingAddressLine1, ShippingAddressLine2, ShippingAddressCity, ShippingAddressCompany, ShippingAddressCountry, ShippingAddressFirstName, ShippingAddressLastName, ShippingAddressPhone, ShippingAddressProvince, ShippingAddressZip, ShippingAddressName, ShippingAddressProvinceCode, ShippingAddressCountryCode, Tags, TaxesIncluded, TotalWeight, SendReceipt, SendFulfillmentReceipt)
VALUES
('123 Main Street', 'Suite #54', 'Memphis', 'Acme, Inc.', 'United States', 'John', 'Doe', '4045559876', 'Tennessee', '38101', 'John Doe', 'GA', 'US', 1, '[{"title":"Super Strong Glue","price":24.99,"grams":"100","quantity":1,"tax_lines":[{"price":13.5,"rate":0.06,"title":"State tax"}]}]', 5945175474276, 'johndoe2@gmail.com', 1, 'pending', null, '#40294', 'This order needs to be expedited, so register it in the system as so.', '4045559876', 'USD', 'USD', '2023-02-27T11:00:00', 'https://referringsite.com', '123 Main Street', 'Suite #54', 'Memphis', 'Acme, Inc.', 'United States', 'John', 'Doe', '4045559876', 'Tennessee', '38101', 'John Doe', 'GA', 'US', NULL, 1, 20, 1, 1)

select * from InventoryLevels 
		--WITH(location_ids='43512280416356, 44648752676964, ..... upto 300 to 500 more - until you hit URL limit error')

select * from InventoryLevels WITH (inventory_item_ids='43512280416356, 44648752676964')

select * from InventoryLevels WITH (location_ids='43512280416356, 44648752676964')

select * from InventoryLevels WITH (inventory_item_ids='43512280416356, 44648752676964' , location_ids='111100034, 111100055')

UPDATE InventoryLevels 
SET AvailableAdjustment=488, 
    LocationId=25801916516
WHERE InventoryItemId=43512276942948
WITH(
 Action='Adjust' --or set or connect
, ContineOn404Error=0 
)

UPDATE InventoryLevels 
SET LocationId=25801916516
  ,Available=488 
WHERE InventoryItemId=43512276942948
WITH(
 Action='set' --or adjust or connect
, ContineOn404Error=0 
)

--OR--
/*
INSERT INTO InventoryLevels (InventoryItemId,LocationId,Available)
VALUES(43512276942948, 25801916516, 488)
--WITH( ContineOn404Error=0 )
*/

UPDATE InventoryLevels 
SET LocationId=25801916516
WHERE InventoryItemId=43512276942948
WITH(
 Action='connect' --or adjust or set
, ContineOn404Error=0 
)

SELECT * FROM generic_request 
WITH (
    URL='/inventory_levels/set.json'
  --OR Use full URL
  --URL='https://MY-STORE-HERE.myshopify.com/admin/api/2023-01/inventory_levels/set.json'
  	
  , RequestMethod='POST'
  , Body='{"location_id":25801916516,"inventory_item_id":43512280416356,"available":42}' --needed if you call PUT, POST
  , Filter='$.inventory_level' --change table name here
  , Headers='Content-Type: application/json'
  , Meta='inventory_item_id:long; location_id:long; available:int; updated_at: datetime'
)

select * from InventoryItems Where Id=43512280416356

select * from InventoryItems Where Id=43512280416356

select * from InventoryItems WITH(Ids='43512280416356, 43512280449124')

UPDATE InventoryItems
SET Cost='25.55'
WHERE Id=43512280416356

SELECT * FROM generic_request 
WITH (
    URL='/graphql.json'
  --OR Use full URL
  --URL='https://MY-STORE-HERE.myshopify.com/admin/api/2023-10/graphql.json'
  
  , RequestMethod='POST'
  , Filter='$.data.products.nodes' --change table name here e.g. products
  , Headers='Content-Type: application/json'
  --change table name and columns below here e.g. products... and id, title etc
  -- change pagesize if needed (i.e. max 250)
  , Body='{
 "query" : "<<{
 
 products(first: 250 [$tag$])
 {
    nodes {
      id
      title
      createdAt
    }
    
    pageInfo {
      hasNextPage
      endCursor
    }
    
  }
  
},FUN_JSONENC>>"
}'
	, NextUrlAttributeOrExpr='$.data.products.pageInfo.endCursor' --change table name 
	, NextUrlEndIndicator='false'
	, StopIndicatorAttributeOrExpr='$.data.products.pageInfo.hasNextPage' --change table name 
	, UseConnection='True'
	, EnablePageTokenForBody='True'
	, HasDifferentNextPageInfo='True'
	, NextPageBodyPart='after: \"[$pagetoken$]\"'
	--Use metadata to speed up execution. To get Metadata Run query without Meta clause. 
	-- Then click View Metadata button found in Botttom Result Grid Toolbar. Get Compact format and paste below
	--, Meta='id:String(255); title:String(255); createdAt:DateTime; '
)

SELECT * FROM generic_request 
WITH (
    URL='/products.json'
  --OR Use full URL
  --URL='https://MY-STORE-HERE.myshopify.com/admin/api/2023-01/products.json'
  	
  , RequestMethod='GET'
  , Body='{}' --needed if you call PUT, POST
  , Filter='$.products[*]' --change table name here
  , Headers='Content-Type: application/json'
  , PagingMode='ByResponseHeaderRfc5988'
  
  
  --Use metadata to speed up execution. To get Metadata Run query without Meta clause. 
  --Then click View Metadata button found in Botttom Result Grid Toolbar. Get Compact format and paste below
  , Meta='id:String(255); title:String(255); created_at:DateTime; '
)

Conclusion

In this article we discussed how to connect to Shopify in Azure Data Factory (Pipeline) and integrate data without any coding. Click here to Download Shopify Connector for Azure Data Factory (Pipeline) and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).

Download Shopify Connector for Azure Data Factory (Pipeline) Documentation 

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JSON

JSON File

XML

SOAP

XML File

JDBC-ODBC Bridge

Salesforce

CSV

Amazon S3 JSON File

Amazon S3 XML File

Amazon S3 CSV File

Azure Blob JSON File

Azure Blob XML File

Azure Blob CSV File

FTP/SFTP JSON File

FTP/SFTP XML File

FTP/SFTP CSV File

Build your own Custom API Connector

Download Shopify Connector for Azure Data Factory (Pipeline) Documentation

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