Shopify Connector for SQL Server In this article you will learn how to integrate Shopify data in SQL Server 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 SQL Server. 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 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 (Pipeline) 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

Video Tutorial - Integrate Shopify data in SQL Server

This video covers following and more so watch carefully. After watching this video follow the steps described in this article.

• How to download / install required driver for Shopify integration in SQL Server
• How to configure connection for Shopify
• Features about API Driver (Authentication / Query Language / Examples / Driver UI)
• Using Shopify Connection in SQL Server

Create Data Source in ZappySys Data Gateway based on API Driver

1. Download and install ZappySys ODBC PowerPack.

2. Search for gateway in start menu and Open ZappySys Data Gateway:
   

3. Go to Users Tab to add our first Gateway user. Click Add; we will give it a name tdsuser and enter password you like to give. Check Admin option and click OK to save. We will use these details later when we create linked server:
   

4. Now we are ready to add a data source. Click Add, give data source a name (Copy this name somewhere, we will need it later) and then select Native - ZappySys API Driver. Finally, click OK. And it will create the Data Set for it and open the ZS driver UI.

   ShopifyDSN

   
   

5. 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

   

6. 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...

   

7. 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:
   

8. Click OK to finish creating the data source.

Read data in SQL Server from the ZappySys Data Gateway

1. To read the data in SQL Server the first thing you have to do is create a Linked Server. Go to SQL Server Management Studio and configure it in a similar way:
   

2. Then click on Security option and configure username we created in ZappySys Data Gateway in one of the previous steps:
   

3. Optional: Under the Server Options, Enable RPC and RPC Out and Disable Promotion of Distributed Transactions(MSDTC).

   

   ---

   You need to enable RPC Out if you plan to use EXEC(...) AT [MY_LINKED_SERVER_NAME] rather than OPENQUERY.
   If don't enabled it, you will encounter the Server 'MY_LINKED_SERVER_NAME' is not configured for RPC error.

   Query Example:

   EXEC('Select * from Products') AT [MY_LINKED_SERVER_NAME]

   ---

   If you plan to use 'INSERT INTO...EXEC(....) AT [MY_LINKED_SERVER_NAME]' in that case you need to Disable Promotion of Distributed Transactions(MSDTC).
   If don't disabled it, you will encounter the The operation could not be performed because OLE DB provider "SQLNCLI11" for linked server "MY_LINKED_SERVER_NAME" was unable to begin a distributed transaction. error.

   Query Example:

   Insert Into dbo.Products
    EXEC('Select * from Products') AT [MY_LINKED_SERVER_NAME]
   

   ---

4. Finally, open a new query and execute a query we saved in one of the previous steps:
   

   SELECT * FROM OPENQUERY([MY_LINKED_SERVER_NAME], 'SELECT * FROM Products');

   

Create Linked Server using Code

    USE [master]
    GO
    --///////////////////////////////////////////////////////////////////////////////////////
    --Run below code in SSMS to create Linked Server and use ZappySys Drivers in SQL Server
    --///////////////////////////////////////////////////////////////////////////////////////

    //Replace YOUR_GATEWAY_USER, YOUR_GATEWAY_PASSWORD
    //Replace localhost with IP/Machine name if ZappySys Gateway Running on different machine other than SQL Server
    //Replace Port 5000 if you configured gateway on a different port


    --1. Configure your gateway service as per this article https://zappysys.com/links?id=10036

    --2. Make sure you have SQL Server Installed. You can download FREE SQL Server Express Edition from here if you dont want to buy Paid version https://www.microsoft.com/en-us/sql-server/sql-server-editions-express

    --Uncomment below if you like to drop linked server if it already exists
    --EXEC master.dbo.sp_dropserver @server=N'LS_ShopifyDSN', @droplogins='droplogins'

    --3. Create new linked server

    EXEC master.dbo.sp_addlinkedserver
      @server = N'LS_ShopifyDSN'  --Linked server name (this will be used in OPENQUERY sql
    , @srvproduct=N''
    ---- For MSSQL 2012,2014,2016 and 2019 use below (SQL Server Native Client 11.0)---
    , @provider=N'SQLNCLI11'
    ---- For MSSQL 2022 or higher use below (Microsoft OLE DB Driver for SQL Server)---
    --, @provider=N'MSOLEDBSQL'
    , @datasrc=N'localhost,5000' --//Machine / Port where Gateway service is running
    , @provstr=N'Network Library=DBMSSOCN;'
    , @catalog=N'ShopifyDSN' --Data source name you gave on Gateway service settings

    --4. Attach gateway login with linked server

    EXEC master.dbo.sp_addlinkedsrvlogin
    @rmtsrvname=N'LS_ShopifyDSN'  --linked server name
    , @useself=N'False'
    , @locallogin=NULL
    , @rmtuser=N'YOUR_GATEWAY_USER' --enter your Gateway user name
    , @rmtpassword='YOUR_GATEWAY_PASSWORD'  --enter your Gateway user's password
    GO

    --5. Enable RPC OUT (This is Optional - Only needed if you plan to use EXEC(...) AT YourLinkedServerName rather than OPENQUERY
    EXEC sp_serveroption 'LS_ShopifyDSN', 'rpc', true;
    EXEC sp_serveroption 'LS_ShopifyDSN', 'rpc out', true;

    --Disable MSDTC - Below needed to support INSERT INTO from EXEC AT statement
    EXEC sp_serveroption 'LS_ShopifyDSN', 'remote proc transaction promotion', false;

    --Increase query timeout if query is going to take longer than 10 mins (Default timeout is 600 seconds)
    --EXEC sp_serveroption 'LS_ShopifyDSN', 'query timeout', 1200;
    GO

Firewall settings

So far we have assumed that Gateway is running on the same machine as SQL Server. However there will be a case when ZappySys ODBC PowerPack is installed on a different machine than SQL Server. In such case you may have to perform additional Firewall configurations. On most computers firewall settings wont allow outside traffic to ZappySys Data Gateway. In such case perform following steps to allow other machines to connect to Gateway.

If you are using newer version of ZappySys Data Gateway then adding firewall rule is just a single click.

1. Search for gateway in start menu and open ZappySys Data Gateway.
2. Go to Firewall Tab and click Add Firewall Rule button like below. This will create Firewall rule to all Inbound Traffic on Port 5000 (Unless you changed it).

1. Search for Windows Firewall Advanced Security in start menu.
2. Under Inbound Rules > Right click and click [New Rule] >> Click Next
3. Select Port on Rule Type >> Click Next
4. Click on TCP and enter port number under specified local port as 5000 (use different one if you changed Default port) >> Click Next
5. Select Profile (i.e. Private, Public) >> Click Next
6. Enter Rule name [i.e. ZappySys Data Gateway – Allow Inbound ] >> Click Next
7. Click OK to save the rule

OPENQUERY vs EXEC (handling larger SQL text)

So far we have seen examples of using OPENQUERY. It allows us to send pass-through query at remote server. The biggest limitation of OPENQUERY is it doesn't allow you to use variables inside SQL so often we have to use unpleasant looking dynamic SQL (Lots of tick, tick …. and escape hell). Well there is good news. With SQL 2005 and later you can use EXEC(your_sql) AT your_linked_server syntax . Disadvantage of EXEC AT is you cannot do SELECT INTO like OPENQUERY. Also you cannot perform JOIN like below in EXEC AT

    SELECT a.* FROM OPENQUERY([ls_ShopifyDSN],'select * from Customers') a
    JOIN OPENQUERY([ls_ShopifyDSN],'select * from Orders') b ON a.CustomerId=b.CustomerId;

    USE [master]
    GO
    --Replace YOUR_GATEWAY_USER, YOUR_GATEWAY_PASSWORD
    --Replace localhost with IP/Machine name if ZappySys Gateway Running on different machine other than SQL Server

    --Create new linked server
    EXEC master.dbo.sp_addlinkedserver
    @server = N'LS_ShopifyDSN'  --Linked server name (this will be used in OPENQUERY sql)
    , @srvproduct=N''
    ---- For MSSQL 2012,2014,2016 and 2019 use below (SQL Server Native Client 11.0)---
    , @provider=N'SQLNCLI11'
    ---- For MSSQL 2022 or higher use below (Microsoft OLE DB Driver for SQL Server)---
    --, @provider=N'MSOLEDBSQL'
    , @datasrc=N'localhost,5000' --//Machine / Port where Gateway service is running
    , @provstr=N'Network Library=DBMSSOCN;'
    , @catalog=N'ShopifyDSN' --Data source name you gave on Gateway service settings

    --Attach gateway login with linked server
    EXEC master.dbo.sp_addlinkedsrvlogin
    @rmtsrvname=N'LS_ShopifyDSN'  --linked server name
    , @useself=N'False'
    , @locallogin=NULL
    , @rmtuser=N'YOUR_GATEWAY_USER' --enter your Gateway user name
    , @rmtpassword='YOUR_GATEWAY_PASSWORD'  --enter your Gateway user's password
    GO

    --5. Enable RPC OUT (This is Optional - Only needed if you plan to use EXEC(...) AT YourLinkedServerName rather than OPENQUERY
    EXEC sp_serveroption 'LS_ShopifyDSN', 'rpc', true;
    EXEC sp_serveroption 'LS_ShopifyDSN', 'rpc out', true;
    --Disable MSDTC - Below needed to support INSERT INTO from EXEC AT statement
    EXEC sp_serveroption 'LS_ShopifyDSN', 'remote proc transaction promotion', false;
    --Increase query timeout if query is going to take longer than 10 mins (Default timeout is 600 seconds)
    --EXEC sp_serveroption 'LS_ShopifyDSN', 'query timeout', 1200;
    GO

Fetching Tables / Columns using metadata stored procs

exec [linked-server-name].[gateway-datasource-name].[DATA].sp_tables

exec [linked-server-name].[gateway-datasource-name].[DATA].sp_columns_90 N'your-table-name'

    //List all tables
    exec [ls_ShopifyDSN].[ShopifyDSN].[DATA].sp_tables

    //List all columns and its type for specified table
    exec [ls_ShopifyDSN].[ShopifyDSN].[DATA].sp_columns_90 N'Account'

Known Issues

Let's explore some common problems that can occur when using OPENQUERY or Data Gateway connectivity.

SQL Native Client 11.0 not visible in the Providers dropdown (Linked Server Creation)

If you are following some screenshots / steps from our article it might say use SQL Native Client to create Linked Server to ZappySys Gateway but for some users they dont see that driver entry in the dropdown. This is due to the fact that Microsoft has deprecated SQL Native Client OLEDB Driver (SQLNCLI and SQLNCLI11) going forward after SQL 2022. So you need to use [Microsoft OLE DB Driver for SQL Server] instead (MSOLEDBSQL). Please follow all other instructions except the driver type selection, use new suggested driver instead if you dont see SQL Native Client.

Error: The data is invalid

There will be a time when, you may encounter unexpected errors like the ones listed below. These can include:

OLE DB provider "SQLNCLI11" for linked server "Zs_Csv" returned message "Deferred prepare could not be completed.".
OLE DB provider "SQLNCLI11" for linked server "Zs_Csv" returned message "Communication link failure".
Msg 13, Level 16, State 1, Line 0

Session Provider: The data is invalid.

There are few reasons for such error but below are two main reasons

• If the query length exceeds 2000 characters, as shown below, you might encounter this error.

  SELECT * FROM OPENQUERY(LS, '--some really long text more than 2000 chars--')

• If a query contains multiple OPENQUERY statements for JOINs or UNIONs, as shown below, it might fail due to a MARS compatibility issue where the gateway doesn't support parallel queries on a single connection.

  SELECT a.id, b.name from OPENQUERY(LS, 'select * from tbl1') a join OPENQUERY(LS, 'select * from tbl2') b on a.id=b.id

There are few ways to fix above error based on reason why you getting this error (i.e. Query Length issue OR JOIN/UNION in the same statement)

• If your query has long SQL (more than 2000 chars ) then reduce SQL length using different techniques
  • e.g. use SELECT * FROM MyTable rather than SELECT col1,col2… FROM MyTable
  • Use Meta Option in WITH clause if you must use column name. (e.g. SELECT * FROM MyTable WITH(META=’c:\meta.txt’) this way you can define column in Meta file rather than SELECT query. Check this article
  • Consider using EXECT (….) AT [Linked_Server_name] option rather than OPENQUERY so you can use very long SQL (See next section on EXEC..AT usecase)
  • Consider using Virtual Table / Stored Proc to wrap long SQL so your call is very small (where usp_GetOrdersByYear is custom proc created on ZappySys Driver UI)
    

    SELECT * FROM OPENQUERY(LS, 'EXEC usp_GetOrdersByYear 2021')

• If your query uses JOIN  / UNION with multiple OPENQUERY in same SQL then use multiple Linked servers (one for each OPENQUERY clause) as below.
  

  select a.id, b.name from OPENQUERY(LS_1, 'select * from tbl1') a join OPENQUERY(LS_2, 'select * from tbl2') b on a.id=b.id

Error: Unable to begin a distributed transaction (When INSERT + EXEC used)

If you try to use the EXEC statement to insert data into a table, as shown below, you might encounter the following error unless the MSDTC option is turned off.

INSERT INTO MyTable EXEC('select * from tbl') AT MyLinkedServer

"Protocol error in TDS stream"
The operation could not be performed because OLE DB provider "SQLNCLI11" for linked server "ls_Json2" was unable to begin a distributed transaction.
--OR--
The operation could not be performed because OLE DB provider "MSOLEDBSQL" for linked server "ls_Json" was unable to begin a distributed transaction.

Solution:
Method-1: Go to linked server properties | Server Options | Enable Promotion of Distributed Transaction | Change to false (Default is true)
Now your try your INSERT with EXEC AT and it should work

Method-2: Run the below command if you dont want to use UI

EXEC master.dbo.sp_serveroption @server=N'My_Linked_Server', @optname=N'remote proc transaction promotion', @optvalue=N'false'

Error: Cannot use OPENQUERY with JOIN / UNION

When you perform a JOIN or UNION ALL on the same Linked Server, it may fail to process sometimes because the Data Gateway doesn't support parallel query requests on the same connection. A workaround for that would be to create multiple linked servers for the same data source. Refer to the section above for the same workaround.

Error: Truncation errors due to data length mismatch

Many times, you may encounter truncation errors if a table column's length is less than the actual column size from the query column. To solve this issue, use the new version of Data Gateway and check the 'Use nvarchar(max) for string options' option found on the General Tab.

Performance Tips

Now, let's look at a few performance tips in this section.

Use INSERT INTO rather than SELECT INTO to avoid extra META request

We discussed some Pros and Cons of OPENQUERY vs EXEC (…) AT in previous section. One obvious advantage of EXEC (….) AT is it reduces number of requests to driver (It sends pass through query). With EXEC you cannot load data dynamically like SELECT INTO tmp FROM OPENQUERY. Table must exist before hand if you use EXEC.

INSERT INTO tmp_API_Report_Load(col1,col2)
EXEC('select col1,col2 from some_api_table') AT [API-LINKED-SERVER]
--OR--
INSERT INTO tmp_API_Report_Load(col1,col2)
select col1,col2 from OPENQUERY([API-LINKED-SERVER], 'select col1,col2 from some_api_table')

The advantage of this method is that your query speed will increase because the system only calls the API once when you use EXEC AT. In contrast, with OPENROWSET, the query needs to be called twice: once to obtain metadata and once to retrieve the data.

Use Cached Metadata if possible

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 SQL Server 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 SQL Server and integrate data without any coding. Click here to Download Shopify Connector for SQL Server 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 SQL Server Documentation 

More integrations

Other application integration scenarios for Shopify

SSIS

Power BI

SSRS

Informatica

MS Access

MS Excel

SSAS

C#

Python

JAVA

Tableau

SAP Crystal Reports

Azure Data Factory (Pipeline)

Azure Data Factory (SSIS)

Talend Studio

UiPath

PowerShell

ODBC

Other connectors for SQL Server

Amazon Ads

Amazon MWS

Amazon Selling Partner (SP-API)

Asana

Azure DevOps

Cosmos DB

DropBox

ElasticSearch

FastSpring

Google BigQuery

Google Calendar

Google Drive

Google Sheets

Hubspot

Jira

Mailchimp

ManagedEngine ServiceDesk Plus (Zoho)

Nativo

OData

OneDrive

Outlook Mail (Office 365)

Power BI

ServiceNow

SharePoint Online

Shopify

Smartsheet

Stripe

YouTube

Zendesk

Zoho CRM

Zoho SalesIQ

Zoom

REST API

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 SQL Server Documentation

Common Searches: